In [1]:
import networkx as nx
import matplotlib.pyplot as plt
import numpy as np
import warnings
from custom import custom_funcs as cf
from datetime import datetime
import random
warnings.filterwarnings('ignore')
%load_ext autoreload
%autoreload 2
%matplotlib inline
In [2]:
#G = cf.load_seventh_grader_network()
#H = nx.read_gpickle('Synthetic Social Network.pkl')
G = nx.gnp_random_graph(100 , 0.05, seed=5001)
G = G.to_directed()
In [3]:
#G.nodes(data=True)
In [4]:
print(len(G.nodes()))
100
In [5]:
#G.edges(data=True)
In [6]:
#G.node[1]
In [7]:
#G.node[21]
In [8]:
#for n in G.nodes():
# del G.node[n]
In [9]:
#G.nodes(data=True)
In [10]:
#G.node[21]['sex']
In [11]:
nx.draw(G)
In [12]:
#del G.node[21]['gender']
In [13]:
#G.edges()
In [14]:
#G = G.to_directed()
In [15]:
#nx.draw(G)
In [16]:
#G.edges()
In [17]:
#for n in G.nodes():
#del G.node[n]['gender']
#print(G.node.items())
In [18]:
#G.nodes(data=True)
In [19]:
import decimal
random.seed(9001)
for n in G.nodes():
temp = round(random.uniform(0, 1), 3)
G.add_node(n,ViRt=temp)
In [20]:
#G.nodes(data=True)
In [21]:
#for n in G.nodes():
# del G.node[n]['gender']
In [22]:
#G.nodes(data=True)
In [23]:
nx.draw(G, with_labels=True)
In [24]:
from circos import CircosPlot
fig = plt.figure(figsize=(6,6))
ax = fig.add_subplot(111)
nodes = sorted(G.nodes())
edges = G.edges()
#node_cmap = {'Male':'blue', 'Female':'red'}
#nodecolors = [node_cmap[G.node[n]['sex']] for n in G.nodes()]
c = CircosPlot(nodes, edges, radius=10, ax=ax, fig=fig)
c.draw()
plt.savefig('images/paper.jpg', dpi=300)
In [25]:
for n in G.nodes():
frnds = len(G.neighbors(n))
G.add_node(n,friends=frnds)
In [26]:
#G.nodes(data=True)
In [27]:
from random import randint
random.seed(9002)
for n in G.nodes():
temp = randint(0,100)
G.add_node(n,uploads=temp)
In [28]:
#G.nodes(data=True)
In [29]:
G.node[21]['friends']
Out[29]:
6
In [30]:
G.node[21]['ViRt']
Out[30]:
0.247
In [31]:
maxi_friends = 0
maxi_uploads = 0
for n in G.nodes():
maxi_friends = max(maxi_friends, G.node[n]['friends'])
maxi_uploads = max(maxi_uploads, G.node[n]['uploads'])
print(maxi_friends)
print(maxi_uploads)
12
99
In [32]:
import math
log_maxi_friends = math.log10(maxi_friends)
#log_maxi_friends = "%.3f" % log_maxi_friends
print(log_maxi_friends)
log_maxi_uploads = math.log10(maxi_uploads)
#log_maxi_uploads = "%.3f" % log_maxi_uploads
print(log_maxi_uploads)
1.0791812460476249
1.99563519459755
In [33]:
AttrCoeff = 0.0
for n in G.nodes():
log_uploads = math.log10(1 + G.node[n]['uploads'])
log_friends = math.log10(1 + G.node[n]['friends'])
bias = math.log10(2)
AttrCoeff = ((log_uploads + log_friends)/(log_maxi_uploads + log_maxi_friends + bias))
AttrCoeff = round(AttrCoeff, 3)
G.add_node(n,Attractiveness_Coeff=AttrCoeff)
In [34]:
G.nodes(data=True)
Out[34]:
[(0,
{'Attractiveness_Coeff': 0.602, 'ViRt': 0.037, 'friends': 2, 'uploads': 35}),
(1,
{'Attractiveness_Coeff': 0.799, 'ViRt': 0.253, 'friends': 5, 'uploads': 82}),
(2,
{'Attractiveness_Coeff': 0.74, 'ViRt': 0.564, 'friends': 6, 'uploads': 44}),
(3,
{'Attractiveness_Coeff': 0.816, 'ViRt': 0.569, 'friends': 6, 'uploads': 80}),
(4,
{'Attractiveness_Coeff': 0.609, 'ViRt': 0.606, 'friends': 5, 'uploads': 18}),
(5,
{'Attractiveness_Coeff': 0.708, 'ViRt': 0.513, 'friends': 4, 'uploads': 48}),
(6,
{'Attractiveness_Coeff': 0.754, 'ViRt': 0.713, 'friends': 7, 'uploads': 43}),
(7,
{'Attractiveness_Coeff': 0.815, 'ViRt': 0.893, 'friends': 5, 'uploads': 93}),
(8,
{'Attractiveness_Coeff': 0.734, 'ViRt': 0.616, 'friends': 3, 'uploads': 74}),
(9,
{'Attractiveness_Coeff': 0.782, 'ViRt': 0.538, 'friends': 5, 'uploads': 72}),
(10,
{'Attractiveness_Coeff': 0.653, 'ViRt': 0.759, 'friends': 4, 'uploads': 31}),
(11,
{'Attractiveness_Coeff': 0.513, 'ViRt': 0.981, 'friends': 5, 'uploads': 8}),
(12,
{'Attractiveness_Coeff': 0.709, 'ViRt': 0.291, 'friends': 3, 'uploads': 61}),
(13,
{'Attractiveness_Coeff': 0.503, 'ViRt': 0.589, 'friends': 9, 'uploads': 4}),
(14,
{'Attractiveness_Coeff': 0.864, 'ViRt': 0.074, 'friends': 8, 'uploads': 91}),
(15,
{'Attractiveness_Coeff': 0.414, 'ViRt': 0.444, 'friends': 4, 'uploads': 4}),
(16,
{'Attractiveness_Coeff': 0.457, 'ViRt': 0.769, 'friends': 4, 'uploads': 6}),
(17,
{'Attractiveness_Coeff': 0.792, 'ViRt': 0.609, 'friends': 4, 'uploads': 93}),
(18,
{'Attractiveness_Coeff': 0.812, 'ViRt': 0.739, 'friends': 8, 'uploads': 60}),
(19,
{'Attractiveness_Coeff': 0.754, 'ViRt': 0.392, 'friends': 4, 'uploads': 69}),
(20,
{'Attractiveness_Coeff': 0.645, 'ViRt': 0.801, 'friends': 5, 'uploads': 24}),
(21,
{'Attractiveness_Coeff': 0.57, 'ViRt': 0.247, 'friends': 6, 'uploads': 11}),
(22,
{'Attractiveness_Coeff': 0.682, 'ViRt': 0.882, 'friends': 2, 'uploads': 66}),
(23,
{'Attractiveness_Coeff': 0.446, 'ViRt': 0.306, 'friends': 7, 'uploads': 3}),
(24,
{'Attractiveness_Coeff': 0.831, 'ViRt': 0.163, 'friends': 8, 'uploads': 70}),
(25,
{'Attractiveness_Coeff': 0.207, 'ViRt': 0.635, 'friends': 4, 'uploads': 0}),
(26,
{'Attractiveness_Coeff': 0.799, 'ViRt': 0.527, 'friends': 6, 'uploads': 70}),
(27,
{'Attractiveness_Coeff': 0.74, 'ViRt': 0.52, 'friends': 6, 'uploads': 44}),
(28,
{'Attractiveness_Coeff': 0.816, 'ViRt': 0.173, 'friends': 5, 'uploads': 94}),
(29,
{'Attractiveness_Coeff': 0.848, 'ViRt': 0.495, 'friends': 8, 'uploads': 80}),
(30,
{'Attractiveness_Coeff': 0.817, 'ViRt': 0.124, 'friends': 6, 'uploads': 81}),
(31,
{'Attractiveness_Coeff': 0.776, 'ViRt': 0.396, 'friends': 7, 'uploads': 51}),
(32,
{'Attractiveness_Coeff': 0.664, 'ViRt': 0.635, 'friends': 6, 'uploads': 24}),
(33,
{'Attractiveness_Coeff': 0.702, 'ViRt': 0.514, 'friends': 4, 'uploads': 46}),
(34,
{'Attractiveness_Coeff': 0.49, 'ViRt': 0.003, 'friends': 4, 'uploads': 8}),
(35,
{'Attractiveness_Coeff': 0.805, 'ViRt': 0.92, 'friends': 8, 'uploads': 57}),
(36,
{'Attractiveness_Coeff': 0.498, 'ViRt': 0.632, 'friends': 5, 'uploads': 7}),
(37,
{'Attractiveness_Coeff': 0.725, 'ViRt': 0.006, 'friends': 9, 'uploads': 27}),
(38,
{'Attractiveness_Coeff': 0.794, 'ViRt': 0.485, 'friends': 9, 'uploads': 47}),
(39,
{'Attractiveness_Coeff': 0.626, 'ViRt': 0.723, 'friends': 4, 'uploads': 25}),
(40,
{'Attractiveness_Coeff': 0.634, 'ViRt': 0.279, 'friends': 2, 'uploads': 45}),
(41,
{'Attractiveness_Coeff': 0.779, 'ViRt': 0.426, 'friends': 5, 'uploads': 70}),
(42,
{'Attractiveness_Coeff': 0.732, 'ViRt': 0.349, 'friends': 4, 'uploads': 58}),
(43,
{'Attractiveness_Coeff': 0.702, 'ViRt': 0.57, 'friends': 2, 'uploads': 77}),
(44,
{'Attractiveness_Coeff': 0.746, 'ViRt': 0.908, 'friends': 4, 'uploads': 65}),
(45,
{'Attractiveness_Coeff': 0.616, 'ViRt': 0.238, 'friends': 5, 'uploads': 19}),
(46,
{'Attractiveness_Coeff': 0.76, 'ViRt': 0.517, 'friends': 3, 'uploads': 91}),
(47,
{'Attractiveness_Coeff': 0.231, 'ViRt': 0.703, 'friends': 2, 'uploads': 1}),
(48,
{'Attractiveness_Coeff': 0.739, 'ViRt': 0.292, 'friends': 7, 'uploads': 38}),
(49,
{'Attractiveness_Coeff': 0.67, 'ViRt': 0.012, 'friends': 2, 'uploads': 60}),
(50,
{'Attractiveness_Coeff': 0.457, 'ViRt': 0.733, 'friends': 4, 'uploads': 6}),
(51,
{'Attractiveness_Coeff': 0.792, 'ViRt': 0.289, 'friends': 7, 'uploads': 58}),
(52,
{'Attractiveness_Coeff': 0.597, 'ViRt': 0.927, 'friends': 3, 'uploads': 25}),
(53,
{'Attractiveness_Coeff': 0.751, 'ViRt': 0.059, 'friends': 3, 'uploads': 85}),
(54,
{'Attractiveness_Coeff': 0.682, 'ViRt': 0.785, 'friends': 2, 'uploads': 66}),
(55,
{'Attractiveness_Coeff': 0.833, 'ViRt': 0.872, 'friends': 7, 'uploads': 80}),
(56,
{'Attractiveness_Coeff': 0.848, 'ViRt': 0.44, 'friends': 7, 'uploads': 90}),
(57,
{'Attractiveness_Coeff': 0.34, 'ViRt': 0.916, 'friends': 6, 'uploads': 1}),
(58,
{'Attractiveness_Coeff': 0.654, 'ViRt': 0.192, 'friends': 6, 'uploads': 22}),
(59,
{'Attractiveness_Coeff': 0.533, 'ViRt': 0.773, 'friends': 6, 'uploads': 8}),
(60,
{'Attractiveness_Coeff': 0.659, 'ViRt': 0.644, 'friends': 5, 'uploads': 27}),
(61,
{'Attractiveness_Coeff': 0.823, 'ViRt': 0.027, 'friends': 5, 'uploads': 99}),
(62,
{'Attractiveness_Coeff': 0.68, 'ViRt': 0.524, 'friends': 5, 'uploads': 32}),
(63,
{'Attractiveness_Coeff': 0.819, 'ViRt': 0.139, 'friends': 5, 'uploads': 96}),
(64,
{'Attractiveness_Coeff': 0.645, 'ViRt': 0.971, 'friends': 4, 'uploads': 29}),
(65,
{'Attractiveness_Coeff': 0.764, 'ViRt': 0.355, 'friends': 3, 'uploads': 94}),
(66,
{'Attractiveness_Coeff': 0.516, 'ViRt': 0.378, 'friends': 4, 'uploads': 10}),
(67,
{'Attractiveness_Coeff': 0.178, 'ViRt': 0.893, 'friends': 3, 'uploads': 0}),
(68,
{'Attractiveness_Coeff': 0.729, 'ViRt': 0.823, 'friends': 5, 'uploads': 47}),
(69,
{'Attractiveness_Coeff': 0.754, 'ViRt': 0.965, 'friends': 7, 'uploads': 43}),
(70,
{'Attractiveness_Coeff': 0.727, 'ViRt': 0.743, 'friends': 4, 'uploads': 56}),
(71,
{'Attractiveness_Coeff': 0.851, 'ViRt': 0.257, 'friends': 7, 'uploads': 92}),
(72,
{'Attractiveness_Coeff': 0.674, 'ViRt': 0.412, 'friends': 3, 'uploads': 46}),
(73,
{'Attractiveness_Coeff': 0.207, 'ViRt': 0.512, 'friends': 4, 'uploads': 0}),
(74,
{'Attractiveness_Coeff': 0.795, 'ViRt': 0.424, 'friends': 6, 'uploads': 68}),
(75,
{'Attractiveness_Coeff': 0.735, 'ViRt': 0.966, 'friends': 3, 'uploads': 75}),
(76,
{'Attractiveness_Coeff': 0.296, 'ViRt': 0.734, 'friends': 1, 'uploads': 4}),
(77,
{'Attractiveness_Coeff': 0.385, 'ViRt': 0.17, 'friends': 3, 'uploads': 4}),
(78,
{'Attractiveness_Coeff': 0.787, 'ViRt': 0.974, 'friends': 4, 'uploads': 90}),
(79,
{'Attractiveness_Coeff': 0.727, 'ViRt': 0.209, 'friends': 4, 'uploads': 56}),
(80,
{'Attractiveness_Coeff': 0.564, 'ViRt': 0.976, 'friends': 9, 'uploads': 7}),
(81,
{'Attractiveness_Coeff': 0.738, 'ViRt': 0.164, 'friends': 4, 'uploads': 61}),
(82,
{'Attractiveness_Coeff': 0.79, 'ViRt': 0.01, 'friends': 7, 'uploads': 57}),
(83,
{'Attractiveness_Coeff': 0.671, 'ViRt': 0.48, 'friends': 7, 'uploads': 22}),
(84,
{'Attractiveness_Coeff': 0.607, 'ViRt': 0.369, 'friends': 7, 'uploads': 13}),
(85,
{'Attractiveness_Coeff': 0.783, 'ViRt': 0.234, 'friends': 4, 'uploads': 87}),
(86,
{'Attractiveness_Coeff': 0.687, 'ViRt': 0.712, 'friends': 3, 'uploads': 51}),
(87,
{'Attractiveness_Coeff': 0.501, 'ViRt': 0.061, 'friends': 6, 'uploads': 6}),
(88,
{'Attractiveness_Coeff': 0.178, 'ViRt': 0.664, 'friends': 3, 'uploads': 0}),
(89,
{'Attractiveness_Coeff': 0.63, 'ViRt': 0.102, 'friends': 1, 'uploads': 66}),
(90,
{'Attractiveness_Coeff': 0.768, 'ViRt': 0.11, 'friends': 5, 'uploads': 64}),
(91,
{'Attractiveness_Coeff': 0.857, 'ViRt': 0.82, 'friends': 7, 'uploads': 97}),
(92,
{'Attractiveness_Coeff': 0.711, 'ViRt': 0.165, 'friends': 2, 'uploads': 83}),
(93,
{'Attractiveness_Coeff': 0.82, 'ViRt': 0.478, 'friends': 5, 'uploads': 97}),
(94,
{'Attractiveness_Coeff': 0.819, 'ViRt': 0.85, 'friends': 5, 'uploads': 96}),
(95,
{'Attractiveness_Coeff': 0.801, 'ViRt': 0.335, 'friends': 6, 'uploads': 71}),
(96,
{'Attractiveness_Coeff': 0.555, 'ViRt': 0.233, 'friends': 4, 'uploads': 14}),
(97,
{'Attractiveness_Coeff': 0.814, 'ViRt': 0.24, 'friends': 12, 'uploads': 42}),
(98,
{'Attractiveness_Coeff': 0.707, 'ViRt': 0.711, 'friends': 3, 'uploads': 60}),
(99,
{'Attractiveness_Coeff': 0.748, 'ViRt': 0.499, 'friends': 6, 'uploads': 47})]
In [35]:
#G.edges(data=True)
In [36]:
#for v1,v2,a in G.edges(data=True):
# G[v1][v2]['count'] = 1
In [37]:
#G.edges(data=True)
In [38]:
import pandas as pd
import numpy as np
df = pd.read_excel("Video_Prop2.xlsx")
df.head()
Out[38]:
video ID
uploader
age
category
length
views
video rating(on a scale of 5)
number of ratings
number of comments
Pi
0
bG-a5ZSdO2I
PhilipDeFranco
1125
Entertainment
73
21180
4.72
418
213
NaN
1
46wXWDiigE8
PhilipDeFranco
1120
Pets & Animals
36
12906
4.80
359
139
NaN
2
X5h6xg7BcbQ
PhilipDeFranco
1116
Entertainment
149
14477
4.76
462
182
NaN
3
VKavlhLlZHc
ditzystef
1122
People & Blogs
88
988
4.83
24
35
NaN
4
DgGZL_rAR8U
PhilipDeFranco
1115
Entertainment
516
22156
4.71
511
237
NaN
In [39]:
df.columns[[0, 2]]
Out[39]:
Index(['video ID', 'age'], dtype='object')
In [40]:
df.drop(df.columns[[1,2,3,4,8,9]], axis=1, inplace=True)
In [41]:
df.head()
Out[41]:
video ID
views
video rating(on a scale of 5)
number of ratings
0
bG-a5ZSdO2I
21180
4.72
418
1
46wXWDiigE8
12906
4.80
359
2
X5h6xg7BcbQ
14477
4.76
462
3
VKavlhLlZHc
988
4.83
24
4
DgGZL_rAR8U
22156
4.71
511
In [42]:
df.rename(columns={'video ID': 'id', 'views': 'nviews', 'video rating(on a scale of 5)': 'rating', 'number of ratings': 'nrating'}, inplace=True)
In [43]:
df.head()
Out[43]:
id
nviews
rating
nrating
0
bG-a5ZSdO2I
21180
4.72
418
1
46wXWDiigE8
12906
4.80
359
2
X5h6xg7BcbQ
14477
4.76
462
3
VKavlhLlZHc
988
4.83
24
4
DgGZL_rAR8U
22156
4.71
511
In [44]:
for a,b in df.iterrows():
print(a,b)
0 id bG-a5ZSdO2I
nviews 21180
rating 4.72
nrating 418
Name: 0, dtype: object
1 id 46wXWDiigE8
nviews 12906
rating 4.8
nrating 359
Name: 1, dtype: object
2 id X5h6xg7BcbQ
nviews 14477
rating 4.76
nrating 462
Name: 2, dtype: object
3 id VKavlhLlZHc
nviews 988
rating 4.83
nrating 24
Name: 3, dtype: object
4 id DgGZL_rAR8U
nviews 22156
rating 4.71
nrating 511
Name: 4, dtype: object
5 id CIm4ci3Y6iM
nviews 19370
rating 4.71
nrating 741
Name: 5, dtype: object
6 id GOrNw5IeEB8
nviews 51416
rating 4.46
nrating 778
Name: 6, dtype: object
7 id LyuwSEYBAPg
nviews 528109
rating 4.45
nrating 3688
Name: 7, dtype: object
8 id wzs4NzyWVB0
nviews 15837
rating 4.36
nrating 511
Name: 8, dtype: object
9 id Z-ZP7Jt-RUM
nviews 16480
rating 4.62
nrating 419
Name: 9, dtype: object
10 id Nj_7al31XU0
nviews 15041
rating 4.76
nrating 393
Name: 10, dtype: object
11 id tsUb3KqRvfE
nviews 81562
rating 4.62
nrating 1175
Name: 11, dtype: object
12 id MngJSNXswlk
nviews 127
rating 3
nrating 2
Name: 12, dtype: object
13 id CFtCgK4lmBk
nviews 23002
rating 4.3
nrating 187
Name: 13, dtype: object
14 id kKWSo5v8EMM
nviews 26066
rating 3.37
nrating 466
Name: 14, dtype: object
15 id yKTK35hL98o
nviews 678416
rating 4.2
nrating 5169
Name: 15, dtype: object
16 id kCrdGejdkdo
nviews 1065650
rating 4.14
nrating 4841
Name: 16, dtype: object
17 id X3EFDr2kLdQ
nviews 8184
rating 4.53
nrating 182
Name: 17, dtype: object
18 id AW4nqnulSZY
nviews 53778
rating 4.55
nrating 411
Name: 18, dtype: object
19 id eLNY4hEcqpk
nviews 99726
rating 3.31
nrating 776
Name: 19, dtype: object
20 id ASVQFzJ47uA
nviews 1680
rating 4.2
nrating 10
Name: 20, dtype: object
21 id hOY3i0i7q0Q
nviews 103209
rating 3.44
nrating 446
Name: 21, dtype: object
22 id Zff52MCWTVA
nviews 25904
rating 4.4
nrating 516
Name: 22, dtype: object
23 id Ir2AiTwCZe8
nviews 539038
rating 4.53
nrating 3696
Name: 23, dtype: object
24 id h1omf3sM_Pw
nviews 214880
rating 4.59
nrating 2562
Name: 24, dtype: object
25 id orcqYIsCtZU
nviews 13751
rating 3.3
nrating 348
Name: 25, dtype: object
26 id O5WcNG9czO4
nviews 18073
rating 3.12
nrating 394
Name: 26, dtype: object
27 id 2UdxdWFud6A
nviews 47413
rating 2.53
nrating 704
Name: 27, dtype: object
28 id TbPYpBNHrgw
nviews 694
rating 4
nrating 4
Name: 28, dtype: object
29 id 2dymWpacPJs
nviews 13583
rating 1.76
nrating 45
Name: 29, dtype: object
30 id wULuwIOTfQI
nviews 6819
rating 4.2
nrating 30
Name: 30, dtype: object
31 id QkqPv7MA5X8
nviews 3893
rating 3.77
nrating 26
Name: 31, dtype: object
32 id 6AmxWrgSdQ4
nviews 232250
rating 4.61
nrating 3536
Name: 32, dtype: object
33 id t-MZjytO2LY
nviews 3683
rating 4.19
nrating 67
Name: 33, dtype: object
34 id w7CygpIOH8c
nviews 140045
rating 4.65
nrating 3121
Name: 34, dtype: object
35 id q7-e-kG6we4
nviews 206036
rating 4.47
nrating 3968
Name: 35, dtype: object
36 id Laty8qc5OJ4
nviews 176557
rating 4.53
nrating 4397
Name: 36, dtype: object
37 id xlegxGXrexw
nviews 16260
rating 4.89
nrating 725
Name: 37, dtype: object
38 id Vjjjjbn9fco
nviews 15140
rating 3.75
nrating 362
Name: 38, dtype: object
39 id LKtAg3JHhtU
nviews 4784
rating 4.8
nrating 15
Name: 39, dtype: object
40 id Mfwth3MFuKY
nviews 65116
rating 4.14
nrating 326
Name: 40, dtype: object
41 id 8tLtWD8sqxs
nviews 65286
rating 4.11
nrating 66
Name: 41, dtype: object
42 id E66gb9pSQi0
nviews 21659
rating 4.09
nrating 34
Name: 42, dtype: object
43 id YfJmtrKi5lE
nviews 14843
rating 0
nrating 0
Name: 43, dtype: object
44 id T5v76P3QUDQ
nviews 802754
rating 3.43
nrating 1731
Name: 44, dtype: object
45 id wJSlSb8Iu80
nviews 66126
rating 4.75
nrating 67
Name: 45, dtype: object
46 id JMihF1u0l6k
nviews 32533
rating 4.56
nrating 9
Name: 46, dtype: object
47 id PIVgmvwAaeQ
nviews 177946
rating 4.13
nrating 168
Name: 47, dtype: object
48 id rDDqP8or9pU
nviews 17781
rating 4.58
nrating 12
Name: 48, dtype: object
49 id IO5B489LHNY
nviews 158040
rating 3.45
nrating 352
Name: 49, dtype: object
50 id _ldkjUIy4Wk
nviews 17211
rating 0
nrating 0
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909 id 7IyOv6Mzuqg
nviews 787
rating 5
nrating 75
Name: 909, dtype: object
910 id mQi1FK927yk
nviews 217
rating 5
nrating 2
Name: 910, dtype: object
911 id uUBPNGnhrCo
nviews 1372
rating 4.46
nrating 13
Name: 911, dtype: object
912 id P-5ajdvhFfE
nviews 1381
rating 0
nrating 0
Name: 912, dtype: object
913 id eHjXT3ZVltc
nviews 1885
rating 0
nrating 0
Name: 913, dtype: object
914 id GomkwlTK-6Q
nviews 286
rating 1
nrating 1
Name: 914, dtype: object
915 id hIkRMqmYwV4
nviews 459
rating 0
nrating 0
Name: 915, dtype: object
916 id w6pIHCyKv9s
nviews 324
rating 5
nrating 2
Name: 916, dtype: object
917 id pr6bGRdtmXA
nviews 2332
rating 4.17
nrating 6
Name: 917, dtype: object
918 id cWm-zt18HLM
nviews 469
rating 0
nrating 0
Name: 918, dtype: object
919 id Ya93B1y3s9g
nviews 7256
rating 3.44
nrating 18
Name: 919, dtype: object
920 id zmZusuBjl_Q
nviews 59311
rating 3.44
nrating 148
Name: 920, dtype: object
921 id -aJ9uNttPM4
nviews 209814
rating 3.17
nrating 47
Name: 921, dtype: object
922 id lmPCDtrt_6Q
nviews 5458
rating 3.29
nrating 35
Name: 922, dtype: object
923 id u37DwMavLNE
nviews 911
rating 4.67
nrating 3
Name: 923, dtype: object
924 id yPkNp3jTJDU
nviews 749
rating 2.67
nrating 3
Name: 924, dtype: object
925 id YDbKuBEgWAQ
nviews 457
rating 0
nrating 0
Name: 925, dtype: object
926 id -CSfqIW1mkA
nviews 1142
rating 1
nrating 1
Name: 926, dtype: object
927 id vW1sY7nyRwo
nviews 821
rating 5
nrating 4
Name: 927, dtype: object
928 id KKsEf2aPnms
nviews 7765
rating 2.95
nrating 19
Name: 928, dtype: object
929 id cS2HsaBA5No
nviews 31507
rating 4.63
nrating 19
Name: 929, dtype: object
930 id zJDuaOINkjE
nviews 346
rating 2
nrating 4
Name: 930, dtype: object
931 id zdh3ZCk4ADw
nviews 804
rating 5
nrating 5
Name: 931, dtype: object
932 id P0PtX1sB16c
nviews 1170
rating 2.6
nrating 5
Name: 932, dtype: object
933 id yXQebNcnoh0
nviews 3306
rating 5
nrating 3
Name: 933, dtype: object
934 id rVkCJX3qghY
nviews 6202
rating 3.76
nrating 17
Name: 934, dtype: object
935 id 3Xr_ocb-_i8
nviews 2451
rating 3.67
nrating 6
Name: 935, dtype: object
936 id T_T9Z_BkAQw
nviews 440
rating 3
nrating 2
Name: 936, dtype: object
937 id B8r6DeHIT9c
nviews 185
rating 0
nrating 0
Name: 937, dtype: object
938 id wL3MkBZCYPQ
nviews 1138
rating 3.67
nrating 6
Name: 938, dtype: object
939 id t_eYmF0W358
nviews 213
rating 3
nrating 1
Name: 939, dtype: object
940 id VqGo6iTAlfc
nviews 992
rating 5
nrating 3
Name: 940, dtype: object
941 id JBNr9QPO9cU
nviews 1416
rating 3.6
nrating 5
Name: 941, dtype: object
942 id fjArlmn5eHY
nviews 10205
rating 3.96
nrating 25
Name: 942, dtype: object
943 id 00B_tSSyIao
nviews 2302
rating 4.25
nrating 12
Name: 943, dtype: object
944 id CuRY5z4CLxY
nviews 24314
rating 2.41
nrating 117
Name: 944, dtype: object
945 id kcA6dZPDOHw
nviews 39509
rating 3.89
nrating 97
Name: 945, dtype: object
946 id KfOiVS9pjsQ
nviews 26606
rating 4.43
nrating 152
Name: 946, dtype: object
947 id -kBIbz-jXrM
nviews 3748480
rating 3.55
nrating 2592
Name: 947, dtype: object
948 id -PCr8CyG1Sg
nviews 1457540
rating 3.72
nrating 2789
Name: 948, dtype: object
949 id wbCcb6NV8Io
nviews 818693
rating 3.24
nrating 1472
Name: 949, dtype: object
950 id LLDj9Y4wvbI
nviews 1634741
rating 4.46
nrating 3916
Name: 950, dtype: object
951 id 6JrRCA-fdd8
nviews 685405
rating 2.54
nrating 344
Name: 951, dtype: object
952 id Odp1FO0Vmuw
nviews 1102281
rating 4.34
nrating 2092
Name: 952, dtype: object
953 id Pd8B-8Au-Wk
nviews 1614321
rating 4.43
nrating 3907
Name: 953, dtype: object
954 id wHirE10GT80
nviews 579548
rating 4.4
nrating 633
Name: 954, dtype: object
955 id smKK8Tzhpso
nviews 200052
rating 4.46
nrating 245
Name: 955, dtype: object
956 id BXnA9FjvLSU
nviews 496368
rating 4.79
nrating 2172
Name: 956, dtype: object
957 id CDx1GLqvBO8
nviews 1060682
rating 4.22
nrating 2964
Name: 957, dtype: object
958 id HBa9wdOANHw
nviews 3654623
rating 4.22
nrating 5328
Name: 958, dtype: object
959 id dls5JTD-uG0
nviews 1262805
rating 3.61
nrating 1808
Name: 959, dtype: object
960 id ledR4xphjmU
nviews 682639
rating 4.07
nrating 1013
Name: 960, dtype: object
961 id em_XyTeNA1g
nviews 1115360
rating 4.58
nrating 3468
Name: 961, dtype: object
962 id M4YsLnIFEr4
nviews 840769
rating 4.31
nrating 1450
Name: 962, dtype: object
963 id yIgoXQWiSlM
nviews 872207
rating 4.34
nrating 1772
Name: 963, dtype: object
964 id x9lwvImJqT0
nviews 362463
rating 4.74
nrating 585
Name: 964, dtype: object
965 id PWgSaBT9hNU
nviews 679546
rating 4.58
nrating 2211
Name: 965, dtype: object
966 id 7E3oIbO0AWE
nviews 1159350
rating 4.42
nrating 5465
Name: 966, dtype: object
967 id 9LEljS3ib84
nviews 773441
rating 4.24
nrating 2280
Name: 967, dtype: object
968 id 2aW2N46vf4Q
nviews 1252307
rating 4.28
nrating 11471
Name: 968, dtype: object
969 id NZNTgglPbUA
nviews 2230729
rating 4.78
nrating 5062
Name: 969, dtype: object
970 id iEuJimaumW4
nviews 107137
rating 4.45
nrating 376
Name: 970, dtype: object
971 id EgJuHNfk7no
nviews 48472
rating 4.68
nrating 259
Name: 971, dtype: object
972 id Cjli_cwkPrw
nviews 28496
rating 4.49
nrating 132
Name: 972, dtype: object
973 id J1bm2GPoFfg
nviews 267270
rating 4.49
nrating 1833
Name: 973, dtype: object
974 id 5fH7c8H6SNw
nviews 1351304
rating 4.64
nrating 1997
Name: 974, dtype: object
975 id BoJJIYWMZlY
nviews 266228
rating 3.09
nrating 2724
Name: 975, dtype: object
976 id nnnjIzamnJo
nviews 43689
rating 4.14
nrating 188
Name: 976, dtype: object
977 id qHAScDFZd8A
nviews 140883
rating 4.56
nrating 507
Name: 977, dtype: object
978 id tvj7Q9LRAJo
nviews 74607
rating 4.75
nrating 294
Name: 978, dtype: object
979 id 1kxE6lftTWU
nviews 117656
rating 4.74
nrating 1296
Name: 979, dtype: object
980 id 9yTgbZSATTU
nviews 74662
rating 4.75
nrating 1819
Name: 980, dtype: object
981 id 3RpNSF-er88
nviews 41594
rating 4.28
nrating 39
Name: 981, dtype: object
982 id e0d_KG7I6o8
nviews 26040
rating 4.51
nrating 73
Name: 982, dtype: object
983 id 4oYjsVdm7dE
nviews 144460
rating 4.51
nrating 1538
Name: 983, dtype: object
984 id b5JVYTxjmdc
nviews 260737
rating 4.61
nrating 2017
Name: 984, dtype: object
985 id iFqYf-ID5oY
nviews 168269
rating 4.63
nrating 1777
Name: 985, dtype: object
986 id puWqNJI8Mjo
nviews 265434
rating 4.64
nrating 1646
Name: 986, dtype: object
987 id GzJ9B7Nnc9E
nviews 9165
rating 4.52
nrating 27
Name: 987, dtype: object
988 id unm8YRN7GmI
nviews 8261
rating 3.5
nrating 22
Name: 988, dtype: object
989 id oULWE4-3Ot8
nviews 7587
rating 3.66
nrating 38
Name: 989, dtype: object
990 id BGa8pYhfar8
nviews 2640
rating 1.61
nrating 18
Name: 990, dtype: object
991 id xiY7T8IivHY
nviews 3434
rating 2.15
nrating 13
Name: 991, dtype: object
992 id x6Xoxaf1Al0
nviews 321869
rating 4.6
nrating 432
Name: 992, dtype: object
993 id sueAQB3fjqo
nviews 389541
rating 3.82
nrating 520
Name: 993, dtype: object
994 id stVmEmJ666M
nviews 505656
rating 4.59
nrating 1447
Name: 994, dtype: object
995 id NWwrEEP8EBk
nviews 156873
rating 4.38
nrating 326
Name: 995, dtype: object
996 id pow5_UYKaJ8
nviews 157314
rating 4.74
nrating 600
Name: 996, dtype: object
997 id eQuIhJId1JY
nviews 265243
rating 3.4
nrating 859
Name: 997, dtype: object
998 id QF4CQeK91bk
nviews 25368
rating 3.37
nrating 186
Name: 998, dtype: object
999 id t2axP1lWFhg
nviews 125060
rating 3.57
nrating 471
Name: 999, dtype: object
In [45]:
df.loc[df.nrating == 0, 'rating'] = 4
df.tail()
Out[45]:
id
nviews
rating
nrating
995
NWwrEEP8EBk
156873
4.38
326
996
pow5_UYKaJ8
157314
4.74
600
997
eQuIhJId1JY
265243
3.40
859
998
QF4CQeK91bk
25368
3.37
186
999
t2axP1lWFhg
125060
3.57
471
In [46]:
#for a,b in df.iterrows():
#print(b)
In [47]:
ShRi = 0.0
random.seed(9003)
for n in G.nodes():
ShRi = round(random.uniform(0, 1), 3)
G.add_node(n,Sharing_Rate=ShRi)
In [48]:
#G.nodes(data=True)
In [49]:
df['nviews'] += 2
In [50]:
df['iniviews'] = df['nviews']
df['eviews'] = df['nviews'] * 1.5
df['eviews'] = df['eviews'].apply(lambda x: int(x))
In [51]:
df.head(10)
Out[51]:
id
nviews
rating
nrating
iniviews
eviews
0
bG-a5ZSdO2I
21182
4.72
418
21182
31773
1
46wXWDiigE8
12908
4.80
359
12908
19362
2
X5h6xg7BcbQ
14479
4.76
462
14479
21718
3
VKavlhLlZHc
990
4.83
24
990
1485
4
DgGZL_rAR8U
22158
4.71
511
22158
33237
5
CIm4ci3Y6iM
19372
4.71
741
19372
29058
6
GOrNw5IeEB8
51418
4.46
778
51418
77127
7
LyuwSEYBAPg
528111
4.45
3688
528111
792166
8
wzs4NzyWVB0
15839
4.36
511
15839
23758
9
Z-ZP7Jt-RUM
16482
4.62
419
16482
24723
In [52]:
sorted([(n,G.neighbors(n)) for n in G.nodes()], key=lambda x: len(x[1]), reverse=True)
Out[52]:
[(97, [32, 33, 37, 65, 73, 75, 13, 14, 18, 9, 25, 94]),
(13, [0, 16, 67, 20, 21, 97, 72, 9, 14]),
(37, [1, 18, 83, 5, 54, 97, 71, 34, 21]),
(38, [82, 35, 69, 12, 74, 10, 76, 66, 61]),
(80, [48, 2, 83, 52, 39, 24, 41, 78, 95]),
(14, [97, 82, 30, 46, 59, 13, 94, 29]),
(18, [97, 99, 21, 22, 56, 37, 69, 51]),
(24, [80, 35, 21, 8, 11, 12, 30, 95]),
(29, [48, 56, 83, 23, 88, 90, 14, 15]),
(35, [24, 66, 3, 38, 56, 44, 60, 31]),
(6, [48, 36, 86, 7, 26, 75, 15]),
(23, [1, 2, 56, 61, 29, 94, 63]),
(31, [33, 2, 35, 4, 69, 55, 91]),
(48, [16, 80, 5, 6, 29, 45, 85]),
(51, [96, 1, 2, 21, 74, 44, 18]),
(55, [65, 87, 40, 25, 27, 62, 31]),
(56, [81, 18, 35, 23, 57, 29, 95]),
(69, [16, 18, 67, 38, 39, 90, 31]),
(71, [32, 1, 98, 84, 37, 58, 59]),
(82, [96, 4, 38, 87, 91, 28, 14]),
(83, [80, 68, 37, 7, 26, 29, 15]),
(84, [16, 81, 3, 36, 71, 57, 47]),
(91, [17, 82, 11, 49, 27, 60, 31]),
(2, [80, 51, 87, 23, 11, 31]),
(3, [99, 35, 84, 89, 57, 62]),
(21, [18, 51, 37, 24, 13, 77]),
(26, [19, 50, 83, 6, 70, 61]),
(27, [32, 20, 86, 55, 91, 92]),
(30, [24, 68, 25, 88, 73, 14]),
(32, [97, 34, 71, 57, 27, 79]),
(57, [32, 1, 3, 84, 56, 93]),
(58, [53, 22, 71, 42, 90, 46]),
(59, [4, 46, 87, 41, 71, 14]),
(74, [51, 19, 36, 38, 20, 28]),
(87, [2, 55, 10, 59, 60, 82]),
(95, [80, 24, 36, 56, 4, 11]),
(99, [18, 3, 36, 44, 77, 79]),
(1, [23, 57, 51, 37, 71]),
(4, [31, 81, 82, 59, 95]),
(7, [28, 83, 52, 77, 6]),
(9, [97, 52, 13, 78, 85]),
(11, [24, 39, 2, 91, 95]),
(20, [66, 27, 74, 93, 13]),
(28, [74, 19, 82, 70, 7]),
(36, [74, 99, 84, 6, 95]),
(41, [80, 19, 59, 68, 73]),
(45, [48, 17, 85, 64, 25]),
(60, [33, 50, 91, 35, 87]),
(61, [26, 50, 66, 38, 23]),
(62, [64, 65, 50, 3, 55]),
(63, [96, 43, 92, 93, 23]),
(68, [8, 41, 83, 53, 30]),
(90, [58, 42, 34, 69, 29]),
(93, [12, 20, 57, 70, 63]),
(94, [72, 97, 23, 14, 47]),
(5, [48, 73, 67, 37]),
(10, [33, 44, 38, 87]),
(15, [75, 83, 29, 6]),
(16, [48, 84, 13, 69]),
(17, [96, 98, 91, 45]),
(19, [41, 26, 28, 74]),
(25, [97, 45, 30, 55]),
(33, [97, 10, 60, 31]),
(34, [32, 90, 37, 78]),
(39, [80, 11, 69, 54]),
(42, [0, 58, 90, 70]),
(44, [51, 10, 99, 35]),
(50, [26, 60, 61, 62]),
(64, [62, 45, 86, 79]),
(66, [35, 20, 61, 38]),
(70, [26, 28, 42, 93]),
(73, [41, 5, 30, 97]),
(78, [80, 9, 34, 88]),
(79, [32, 64, 99, 85]),
(81, [56, 49, 4, 84]),
(85, [48, 9, 45, 79]),
(96, [17, 82, 51, 63]),
(8, [24, 40, 68]),
(12, [24, 93, 38]),
(46, [58, 59, 14]),
(52, [80, 9, 7]),
(53, [58, 68, 98]),
(65, [97, 62, 55]),
(67, [13, 5, 69]),
(72, [43, 13, 94]),
(75, [97, 6, 15]),
(77, [99, 21, 7]),
(86, [64, 27, 6]),
(88, [30, 29, 78]),
(98, [17, 53, 71]),
(0, [42, 13]),
(22, [18, 58]),
(40, [8, 55]),
(43, [72, 63]),
(47, [84, 94]),
(49, [81, 91]),
(54, [37, 39]),
(92, [27, 63]),
(76, [38]),
(89, [3])]
In [53]:
df.ix[8]
Out[53]:
id wzs4NzyWVB0
nviews 15839
rating 4.36
nrating 511
iniviews 15839
eviews 23758
Name: 8, dtype: object
In [54]:
random.seed(9004)
ShR_thr = 1.5
VwR_thr = 1
nodeSt = 0
rate = 0
pardaught = dict()
exclu = list()
connected = list()
queue = [nodeSt]
visited_nodes = set()
path = set()
connected.append(nodeSt)
for node in queue:
if node == nodeSt:
df.ix[8,'nviews'] += 1
df.ix[8,'eviews'] += 1
rate = randint(1,5)
#df.ix[8,'rating'] += 1
r = df.ix[8,'rating']
df.ix[8,'rating'] = ((df.ix[8,'nrating'] * r) + rate)/float(df.ix[8,'nrating'] + 1)
df.ix[8,'nrating'] += 1
#print(G.node[node])
neighbors = G.neighbors(node)
#exclu = [n for n in neighbors if n not in visited_nodes]
exclu = [n for n in neighbors if n not in connected]
pardaught[node] = exclu
connected.extend(exclu)
#queue.remove(node)
visited_nodes.add(node)
path.add(node)
queue.extend(exclu)
df.ix[8,'eviews'] += len(neighbors)
print(str(node) + " viewed & shared")
else:
for key, values in pardaught.items():
if node in values:
parent = key
if VwR_thr <= (df.ix[8,'rating']*G.node[node]['ViRt']*G.node[parent]['Attractiveness_Coeff']):
df.ix[8,'nviews'] += 1
df.ix[8,'eviews'] += 1
print(str(node) + " viewed")
rate = randint(1,5)
r = df.ix[8,'rating']
df.ix[8,'rating'] = ((df.ix[8,'nrating'] * r) + rate)/float(df.ix[8,'nrating'] + 1)
df.ix[8,'nrating'] += 1
if ShR_thr <= (df.ix[8,'rating']*G.node[node]['Sharing_Rate']*G.node[parent]['Attractiveness_Coeff']):
#print(G.node[node])
neighbors = G.neighbors(node)
exclu = [n for n in neighbors if n not in connected]
pardaught[node] = exclu
connected.extend(exclu)
#queue.remove(node)
visited_nodes.add(node)
path.add(node)
queue.extend(exclu)
df.ix[8,'eviews'] += len(neighbors)
print(str(node) + " shared")
#print(connected)
0 viewed & shared
13 viewed
13 shared
16 viewed
67 viewed
20 viewed
97 shared
9 viewed
32 viewed
32 shared
33 viewed
37 shared
65 viewed
65 shared
73 viewed
73 shared
75 viewed
18 viewed
18 shared
25 viewed
94 viewed
34 shared
71 shared
57 viewed
57 shared
27 viewed
79 shared
1 shared
83 viewed
5 viewed
5 shared
54 viewed
62 viewed
62 shared
55 viewed
99 viewed
99 shared
22 viewed
56 viewed
69 viewed
51 viewed
51 shared
78 viewed
98 viewed
98 shared
84 viewed
59 viewed
64 viewed
64 shared
23 viewed
48 shared
50 viewed
50 shared
36 viewed
44 viewed
96 shared
2 viewed
74 viewed
74 shared
17 viewed
53 shared
86 viewed
80 viewed
80 shared
6 viewed
6 shared
29 viewed
26 viewed
26 shared
60 viewed
61 shared
82 shared
19 viewed
38 viewed
38 shared
28 shared
68 viewed
68 shared
52 viewed
52 shared
39 viewed
7 viewed
7 shared
15 viewed
70 viewed
70 shared
66 viewed
66 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
35 viewed
10 viewed
76 viewed
8 viewed
31 viewed
81 shared
11 viewed
11 shared
49 shared
In [55]:
df.ix[8]
Out[55]:
id wzs4NzyWVB0
nviews 15900
rating 4.23594
nrating 572
iniviews 15839
eviews 24049
Name: 8, dtype: object
In [56]:
newG = G.subgraph(path)
nx.draw(newG, with_labels=True)
In [57]:
pardaught
Out[57]:
{0: [42, 13],
1: [23],
4: [31, 81],
5: [48],
6: [7, 15],
7: [],
11: [],
13: [16, 67, 20, 21, 97, 72, 9, 14],
18: [99, 22, 56, 69, 51],
26: [70],
28: [],
32: [34, 71, 57, 27, 79],
34: [90, 78],
37: [1, 83, 5, 54],
38: [35, 12, 10, 76],
48: [80, 6, 29],
49: [],
50: [26, 60, 61],
51: [96, 2, 74],
52: [],
53: [68],
57: [3, 93],
61: [66],
62: [50],
64: [45, 86],
65: [62, 55],
66: [],
68: [8],
70: [],
71: [98, 84, 58, 59],
73: [41, 30],
74: [19, 38, 28],
79: [64, 85],
80: [52, 39, 24, 95],
81: [],
82: [4, 87, 91],
87: [],
91: [11, 49],
96: [82, 63],
97: [32, 33, 37, 65, 73, 75, 18, 25, 94],
98: [17, 53],
99: [36, 44, 77]}
In [58]:
lst = list()
for key, values in pardaught.items():
lst.extend(values)
print(lst)
[42, 13, 62, 55, 8, 17, 53, 7, 15, 98, 84, 58, 59, 45, 86, 41, 30, 19, 38, 28, 16, 67, 20, 21, 97, 72, 9, 14, 64, 85, 52, 39, 24, 95, 99, 22, 56, 69, 51, 31, 81, 70, 11, 49, 48, 34, 71, 57, 27, 79, 32, 33, 37, 65, 73, 75, 18, 25, 94, 90, 78, 36, 44, 77, 23, 1, 83, 5, 54, 35, 12, 10, 76, 4, 87, 91, 82, 63, 80, 6, 29, 26, 60, 61, 96, 2, 74, 68, 3, 93, 66, 50]
In [59]:
print(len(lst))
myset=set(lst)
print(len(myset))
92
92
In [60]:
#H = G.to_undirected()
In [61]:
#H.edges()
In [62]:
nx.shortest_path(G, 4, 14)
Out[62]:
[4, 82, 14]
In [63]:
def path_exists(node1, node2, G):
visited_nodes = set()
queue = [node1]
for node in queue:
neighbors = G.neighbors(node)
if node2 in neighbors:
print('Path exists between nodes {0} and {1}'.format(node1, node2))
return True
else:
queue.remove(node)
visited_nodes.add(node)
queue.extend([n for n in neighbors if n not in visited_nodes])
if len(queue) == 0:
print('Path does not exist between nodes {0} and {1}'.format(node1, node2))
return False
In [64]:
def test_path_exists():
print(path_exists(18, 5, G))
print(path_exists(29, 26, G))
test_path_exists()
Path exists between nodes 18 and 5
True
Path exists between nodes 29 and 26
True
In [65]:
nx.has_path(G, 29, 26)
Out[65]:
True
In [66]:
def extract_path_edges(G, source, target):
if nx.has_path(G, source, target):
shor = nx.shortest_path(G, source, target)
newG = G.subgraph(shor)
return newG
else:
raise Exception('Path does not exist between nodes {0} and {1}.'.format(source, target))
newG = extract_path_edges(G, 1, 14)
nx.draw(newG, with_labels=True)
In [67]:
#df[min(df['nviews'])]
nx.draw(G)
In [68]:
df['nviews'].argmin()
Out[68]:
276
In [69]:
df.ix[276]
Out[69]:
id OR6XwtjoKXo
nviews 8
rating 4
nrating 0
iniviews 8
eviews 12
Name: 276, dtype: object
In [70]:
#df[['nviews']]
In [71]:
#df.ix[38,'nviews'] += 1
#df.ix[38,'eviews'] += 1
df.ix[276]
Out[71]:
id OR6XwtjoKXo
nviews 8
rating 4
nrating 0
iniviews 8
eviews 12
Name: 276, dtype: object
In [72]:
G.node[97]['Sharing_Rate']
Out[72]:
0.859
In [73]:
random.seed(9004)
nodeSt = 97
rate = 0
pardaught = dict()
exclu = list()
connected = list()
queue = [nodeSt]
visited_nodes = set()
path = set()
connected.append(nodeSt)
for node in queue:
if node == nodeSt:
df.ix[276,'nviews'] += 1
df.ix[276,'eviews'] += 1
rate = randint(1,5)
r = df.ix[276,'rating']
df.ix[276,'rating'] = ((df.ix[276,'nrating'] * r) + rate)/float(df.ix[276,'nrating'] + 1)
df.ix[276,'nrating'] += 1
#print(G.node[node])
neighbors = G.neighbors(node)
#exclu = [n for n in neighbors if n not in visited_nodes]
exclu = [n for n in neighbors if n not in connected]
pardaught[node] = exclu
#connected |= set(exclu)
connected.extend(exclu)
#queue.remove(node)
visited_nodes.add(node)
path.add(node)
queue.extend(exclu)
df.ix[276,'eviews'] += len(neighbors)
print(str(node) + " viewed & shared")
else:
for key, values in pardaught.items():
if node in values:
parent = key
if VwR_thr <= (df.ix[276,'rating']*G.node[node]['ViRt']*G.node[parent]['Attractiveness_Coeff']):
df.ix[276,'nviews'] += 1
df.ix[276,'eviews'] += 1
print(str(node) + " viewed")
rate = randint(1,5)
r = df.ix[276,'rating']
df.ix[276,'rating'] = ((df.ix[276,'nrating'] * r) + rate)/float(df.ix[276,'nrating'] + 1)
df.ix[276,'nrating'] += 1
if ShR_thr <= (df.ix[276,'rating']*G.node[node]['Sharing_Rate']*G.node[parent]['Attractiveness_Coeff']):
#print(G.node[node])
neighbors = G.neighbors(node)
exclu = [n for n in neighbors if n not in connected]
pardaught[node] = exclu
connected.extend(exclu)
#queue.remove(node)
visited_nodes.add(node)
path.add(node)
queue.extend(exclu)
df.ix[276,'eviews'] += len(neighbors)
print(str(node) + " shared")
97 viewed & shared
32 viewed
32 shared
33 viewed
37 shared
65 viewed
73 viewed
73 shared
75 viewed
13 viewed
13 shared
18 viewed
9 viewed
25 viewed
94 viewed
57 viewed
1 shared
54 viewed
67 viewed
In [74]:
df.ix[276]
Out[74]:
id OR6XwtjoKXo
nviews 22
rating 2.42857
nrating 14
iniviews 8
eviews 71
Name: 276, dtype: object
In [75]:
lst = list()
for key, values in pardaught.items():
lst.extend(values)
print(len(lst))
myset=set(lst)
print(len(myset))
31
31
In [76]:
newG = G.subgraph(path)
nx.draw(newG, with_labels=True)
In [77]:
len(path)
Out[77]:
6
In [78]:
random.seed(5002)
for i in range(100):
nodeSt = randint(0,99)
rate = 0
pardaught = dict()
exclu = list()
connected = list()
queue = [nodeSt]
visited_nodes = set()
vid = randint(0,49)
#print(vid)
path = set()
connected.append(nodeSt)
for node in queue:
if node == nodeSt:
df.ix[vid,'nviews'] += 1
df.ix[vid,'eviews'] += 1
rate = randint(1,5)
r = df.ix[vid,'rating']
df.ix[vid,'rating'] = ((df.ix[vid,'nrating'] * r) + rate)/float(df.ix[vid,'nrating'] + 1)
df.ix[vid,'nrating'] += 1
#print(G.node[node])
neighbors = G.neighbors(node)
#exclu = [n for n in neighbors if n not in visited_nodes]
exclu = [n for n in neighbors if n not in connected]
pardaught[node] = exclu
connected.extend(exclu)
#queue.remove(node)
visited_nodes.add(node)
path.add(node)
queue.extend(exclu)
df.ix[vid,'eviews'] += len(neighbors)
print(str(node) + " viewed & shared")
else:
for key, values in pardaught.items():
if node in values:
parent = key
if VwR_thr <= (df.ix[vid,'rating']*G.node[node]['ViRt']*G.node[parent]['Attractiveness_Coeff']):
df.ix[vid,'nviews'] += 1
df.ix[vid,'eviews'] += 1
print(str(node) + " viewed")
rate = randint(1,5)
r = df.ix[vid,'rating']
df.ix[vid,'rating'] = ((df.ix[vid,'nrating'] * r) + rate)/float(df.ix[vid,'nrating'] + 1)
df.ix[vid,'nrating'] += 1
if ShR_thr <= (df.ix[vid,'rating']*G.node[node]['Sharing_Rate']*G.node[parent]['Attractiveness_Coeff']):
#print(G.node[node])
neighbors = G.neighbors(node)
exclu = [n for n in neighbors if n not in connected]
pardaught[node] = exclu
connected.extend(exclu)
#queue.remove(node)
visited_nodes.add(node)
path.add(node)
queue.extend(exclu)
df.ix[vid,'eviews'] += len(neighbors)
print(str(node) + " shared")
81 viewed & shared
56 viewed
4 viewed
4 shared
84 viewed
82 shared
59 viewed
96 shared
38 viewed
38 shared
87 shared
91 viewed
91 shared
28 shared
14 shared
17 viewed
51 shared
35 viewed
69 viewed
74 viewed
74 shared
10 viewed
76 viewed
66 viewed
66 shared
61 shared
2 viewed
55 viewed
60 viewed
11 viewed
11 shared
27 viewed
19 viewed
70 viewed
70 shared
7 viewed
7 shared
97 shared
30 shared
46 viewed
46 shared
13 viewed
13 shared
94 viewed
29 viewed
1 shared
44 viewed
18 viewed
18 shared
36 viewed
20 viewed
26 viewed
26 shared
50 viewed
50 shared
23 viewed
39 viewed
42 viewed
93 viewed
83 viewed
52 viewed
52 shared
6 viewed
6 shared
32 viewed
32 shared
33 viewed
37 shared
65 viewed
65 shared
73 viewed
73 shared
75 viewed
9 viewed
9 shared
25 viewed
68 viewed
68 shared
88 viewed
88 shared
16 viewed
67 viewed
57 viewed
57 shared
71 shared
99 viewed
99 shared
22 viewed
62 shared
80 viewed
80 shared
48 shared
86 viewed
15 viewed
34 shared
79 shared
5 viewed
5 shared
54 viewed
78 viewed
8 viewed
53 shared
98 viewed
98 shared
64 viewed
64 shared
52 viewed & shared
80 viewed
80 shared
9 viewed
9 shared
7 viewed
7 shared
48 shared
2 viewed
83 viewed
39 viewed
41 viewed
78 viewed
97 shared
13 viewed
13 shared
28 shared
77 shared
6 viewed
6 shared
16 viewed
16 shared
5 viewed
5 shared
29 viewed
32 viewed
32 shared
33 viewed
37 shared
65 viewed
65 shared
73 viewed
73 shared
75 viewed
14 shared
18 viewed
18 shared
25 viewed
94 viewed
67 viewed
20 viewed
74 viewed
74 shared
19 viewed
19 shared
82 shared
70 viewed
70 shared
36 viewed
86 viewed
26 viewed
26 shared
15 viewed
69 viewed
34 shared
71 shared
57 viewed
57 shared
27 viewed
79 shared
1 shared
54 viewed
62 viewed
62 shared
55 viewed
46 viewed
46 shared
59 viewed
22 viewed
56 viewed
51 viewed
51 shared
38 viewed
38 shared
96 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
42 viewed
93 viewed
50 viewed
50 shared
61 shared
98 viewed
98 shared
64 viewed
64 shared
23 viewed
44 viewed
35 viewed
12 viewed
10 viewed
76 viewed
66 viewed
66 shared
17 viewed
31 viewed
81 shared
60 viewed
11 viewed
11 shared
49 shared
53 shared
68 viewed
68 shared
8 viewed
46 viewed & shared
59 viewed
89 viewed & shared
3 viewed
84 viewed & shared
16 viewed
16 shared
81 shared
3 viewed
36 viewed
71 shared
57 viewed
57 shared
47 viewed
48 shared
13 viewed
13 shared
69 viewed
56 viewed
4 viewed
4 shared
32 viewed
32 shared
1 shared
98 viewed
98 shared
37 shared
59 viewed
80 viewed
80 shared
5 viewed
5 shared
6 viewed
6 shared
29 viewed
67 viewed
20 viewed
97 shared
9 viewed
82 shared
34 shared
27 viewed
79 shared
51 shared
17 viewed
53 shared
18 viewed
18 shared
83 viewed
54 viewed
2 viewed
52 viewed
39 viewed
78 viewed
73 viewed
73 shared
86 viewed
7 viewed
7 shared
26 viewed
26 shared
75 viewed
15 viewed
33 viewed
65 viewed
65 shared
25 viewed
94 viewed
96 shared
38 viewed
38 shared
87 shared
91 viewed
91 shared
28 shared
64 viewed
64 shared
99 viewed
99 shared
74 viewed
74 shared
44 viewed
68 viewed
68 shared
22 viewed
19 viewed
50 viewed
50 shared
70 viewed
70 shared
61 shared
62 viewed
62 shared
55 viewed
35 viewed
10 viewed
76 viewed
66 viewed
66 shared
60 viewed
11 viewed
11 shared
8 viewed
44 viewed & shared
51 shared
10 viewed
99 viewed
99 shared
35 viewed
96 shared
1 shared
2 viewed
74 viewed
74 shared
18 viewed
18 shared
3 viewed
36 viewed
79 shared
17 viewed
82 shared
57 viewed
57 shared
37 shared
71 shared
19 viewed
38 viewed
38 shared
20 viewed
28 shared
97 shared
22 viewed
56 viewed
69 viewed
32 viewed
64 viewed
64 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
83 viewed
5 viewed
54 viewed
34 shared
98 viewed
98 shared
59 viewed
76 viewed
66 viewed
66 shared
61 shared
70 viewed
70 shared
7 viewed
7 shared
33 viewed
73 viewed
73 shared
75 viewed
13 viewed
13 shared
9 viewed
9 shared
25 viewed
94 viewed
62 viewed
62 shared
86 viewed
81 shared
55 viewed
60 viewed
11 viewed
11 shared
27 viewed
78 viewed
53 shared
26 viewed
26 shared
50 viewed
50 shared
52 viewed
52 shared
6 viewed
6 shared
16 viewed
67 viewed
39 viewed
68 viewed
68 shared
80 viewed
80 shared
48 shared
15 viewed
8 viewed
29 viewed
34 viewed & shared
32 viewed
78 viewed
75 viewed & shared
97 shared
6 viewed
6 shared
15 viewed
32 viewed
33 viewed
37 shared
73 viewed
73 shared
13 viewed
13 shared
18 viewed
18 shared
9 viewed
9 shared
25 viewed
94 viewed
48 shared
36 viewed
86 viewed
7 viewed
26 viewed
26 shared
1 shared
83 viewed
5 viewed
54 viewed
71 shared
34 shared
16 viewed
67 viewed
20 viewed
99 viewed
99 shared
22 viewed
56 viewed
69 viewed
51 shared
52 viewed
52 shared
78 viewed
80 viewed
80 shared
29 viewed
19 viewed
50 viewed
50 shared
70 viewed
70 shared
61 shared
57 viewed
98 viewed
98 shared
84 viewed
59 viewed
3 viewed
44 viewed
79 shared
96 shared
2 viewed
74 viewed
74 shared
39 viewed
28 shared
93 viewed
66 viewed
66 shared
38 viewed
38 shared
17 viewed
53 shared
64 viewed
64 shared
82 shared
35 viewed
10 viewed
76 viewed
68 viewed
68 shared
4 viewed
87 shared
91 viewed
91 shared
8 viewed
55 viewed
11 viewed
11 shared
27 viewed
31 viewed
35 viewed & shared
44 viewed
99 viewed & shared
18 viewed
18 shared
3 viewed
3 shared
36 viewed
44 viewed
79 shared
97 shared
22 viewed
56 viewed
37 shared
69 viewed
51 viewed
51 shared
35 viewed
84 viewed
57 viewed
57 shared
62 viewed
62 shared
32 viewed
32 shared
64 viewed
64 shared
33 viewed
65 viewed
65 shared
73 viewed
73 shared
75 viewed
13 viewed
13 shared
14 shared
9 viewed
9 shared
25 viewed
94 viewed
1 shared
83 viewed
5 viewed
5 shared
54 viewed
71 shared
34 shared
96 shared
2 viewed
74 viewed
74 shared
50 viewed
50 shared
55 viewed
27 viewed
86 viewed
16 viewed
67 viewed
20 viewed
82 shared
46 viewed
46 shared
59 viewed
29 viewed
52 viewed
52 shared
78 viewed
23 viewed
48 shared
98 viewed
98 shared
17 viewed
19 viewed
19 shared
38 viewed
38 shared
28 shared
26 viewed
26 shared
60 viewed
61 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
80 viewed
80 shared
7 viewed
7 shared
6 viewed
6 shared
53 shared
12 viewed
10 viewed
76 viewed
66 viewed
66 shared
70 viewed
70 shared
31 viewed
81 shared
11 viewed
11 shared
49 shared
39 viewed
15 viewed
68 viewed
68 shared
42 viewed
8 viewed
0 viewed & shared
13 viewed
13 shared
16 viewed
67 viewed
20 viewed
97 shared
9 viewed
32 viewed
32 shared
33 viewed
37 shared
65 viewed
65 shared
73 viewed
73 shared
75 viewed
18 viewed
18 shared
25 viewed
94 viewed
34 shared
71 shared
57 viewed
57 shared
27 viewed
79 shared
1 shared
83 viewed
5 viewed
5 shared
54 viewed
62 viewed
62 shared
55 viewed
99 viewed
99 shared
22 viewed
56 viewed
69 viewed
51 viewed
51 shared
78 viewed
98 viewed
98 shared
84 viewed
59 viewed
64 viewed
64 shared
23 viewed
48 shared
50 viewed
50 shared
36 viewed
44 viewed
96 shared
2 viewed
74 viewed
74 shared
17 viewed
53 shared
86 viewed
80 viewed
80 shared
6 viewed
6 shared
29 viewed
26 viewed
26 shared
60 viewed
61 shared
82 shared
19 viewed
19 shared
38 viewed
38 shared
28 shared
68 viewed
68 shared
52 viewed
52 shared
39 viewed
7 viewed
7 shared
15 viewed
70 viewed
70 shared
66 viewed
66 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
35 viewed
12 viewed
10 viewed
76 viewed
8 viewed
31 viewed
81 shared
11 viewed
11 shared
49 shared
65 viewed & shared
97 shared
62 viewed
62 shared
55 viewed
32 viewed
32 shared
33 viewed
37 shared
73 viewed
73 shared
75 viewed
13 viewed
13 shared
14 shared
18 viewed
18 shared
9 viewed
9 shared
25 viewed
94 viewed
64 viewed
64 shared
50 viewed
50 shared
3 viewed
34 shared
71 shared
57 viewed
27 viewed
79 shared
1 shared
83 viewed
5 viewed
5 shared
54 viewed
16 viewed
67 viewed
20 viewed
82 shared
46 viewed
46 shared
59 viewed
29 viewed
99 viewed
99 shared
22 viewed
56 viewed
69 viewed
51 shared
52 viewed
52 shared
78 viewed
86 viewed
60 viewed
61 shared
98 viewed
98 shared
84 viewed
48 shared
96 shared
4 viewed
4 shared
38 viewed
38 shared
87 shared
91 viewed
91 shared
28 shared
36 viewed
44 viewed
2 viewed
74 viewed
74 shared
80 viewed
80 shared
7 viewed
66 viewed
66 shared
17 viewed
53 shared
6 viewed
6 shared
81 shared
35 viewed
10 viewed
76 viewed
11 viewed
11 shared
19 viewed
70 viewed
70 shared
39 viewed
68 viewed
68 shared
15 viewed
93 viewed
8 viewed
85 viewed & shared
48 shared
9 viewed
9 shared
79 shared
16 viewed
16 shared
80 viewed
80 shared
5 viewed
5 shared
6 viewed
6 shared
29 viewed
97 shared
52 viewed
52 shared
13 viewed
13 shared
78 viewed
32 viewed
32 shared
64 viewed
64 shared
99 viewed
99 shared
69 viewed
2 viewed
83 viewed
39 viewed
41 viewed
73 viewed
73 shared
67 viewed
37 shared
36 viewed
86 viewed
7 viewed
7 shared
26 viewed
26 shared
75 viewed
15 viewed
33 viewed
65 viewed
65 shared
14 shared
18 viewed
18 shared
25 viewed
94 viewed
20 viewed
34 shared
71 shared
57 viewed
57 shared
27 viewed
62 viewed
62 shared
3 viewed
3 shared
44 viewed
1 shared
54 viewed
28 shared
19 viewed
50 viewed
50 shared
70 viewed
70 shared
61 shared
55 viewed
82 shared
46 viewed
46 shared
59 viewed
22 viewed
56 viewed
51 shared
98 viewed
98 shared
35 viewed
23 viewed
74 viewed
74 shared
60 viewed
42 viewed
66 viewed
66 shared
38 viewed
38 shared
96 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
17 viewed
53 shared
10 viewed
76 viewed
31 viewed
81 shared
11 viewed
11 shared
49 shared
68 viewed
68 shared
8 viewed
88 viewed & shared
68 viewed & shared
8 viewed
41 viewed
83 viewed
53 shared
30 shared
98 viewed
98 shared
25 viewed
88 viewed
88 shared
73 viewed
73 shared
17 viewed
71 shared
32 viewed
32 shared
1 shared
84 viewed
37 shared
59 viewed
34 shared
57 viewed
27 viewed
79 shared
51 shared
18 viewed
18 shared
54 viewed
64 viewed
64 shared
99 viewed
99 shared
96 shared
2 viewed
74 viewed
74 shared
44 viewed
22 viewed
56 viewed
69 viewed
62 viewed
62 shared
86 viewed
3 viewed
36 viewed
82 shared
19 viewed
38 viewed
38 shared
20 viewed
28 shared
50 viewed
55 viewed
4 viewed
4 shared
87 shared
91 viewed
91 shared
35 viewed
10 viewed
76 viewed
66 viewed
66 shared
61 shared
70 viewed
70 shared
7 viewed
7 shared
81 shared
60 viewed
11 viewed
11 shared
26 viewed
26 shared
93 viewed
52 viewed
52 shared
6 viewed
6 shared
39 viewed
80 viewed
80 shared
9 viewed
48 shared
75 viewed
15 viewed
16 viewed
16 shared
13 shared
67 viewed
22 viewed & shared
18 viewed
18 shared
97 shared
99 viewed
99 shared
56 viewed
37 shared
69 viewed
51 shared
32 viewed
32 shared
33 viewed
65 viewed
65 shared
73 viewed
73 shared
75 viewed
13 viewed
13 shared
9 viewed
9 shared
25 viewed
94 viewed
3 viewed
36 viewed
44 viewed
79 shared
1 shared
83 viewed
5 viewed
54 viewed
71 shared
34 shared
96 shared
2 viewed
74 viewed
74 shared
57 viewed
27 viewed
62 viewed
62 shared
55 viewed
16 viewed
67 viewed
20 viewed
52 viewed
52 shared
78 viewed
64 viewed
64 shared
98 viewed
98 shared
59 viewed
17 viewed
82 shared
38 viewed
38 shared
28 shared
50 viewed
80 viewed
80 shared
7 viewed
86 viewed
53 shared
4 viewed
87 shared
91 viewed
91 shared
35 viewed
10 viewed
76 viewed
66 shared
61 shared
70 viewed
70 shared
39 viewed
68 viewed
68 shared
60 viewed
11 viewed
11 shared
31 viewed
26 viewed
26 shared
93 viewed
8 viewed
6 viewed
6 shared
15 viewed
64 viewed & shared
62 viewed
62 shared
86 viewed
79 shared
50 viewed
3 viewed
55 viewed
32 viewed
99 viewed
99 shared
18 viewed
18 shared
36 viewed
44 viewed
97 shared
22 viewed
56 viewed
37 shared
69 viewed
51 shared
33 viewed
73 viewed
73 shared
75 viewed
13 viewed
13 shared
9 viewed
25 viewed
94 viewed
1 shared
5 viewed
54 viewed
71 shared
34 shared
2 viewed
74 shared
16 viewed
67 viewed
20 viewed
57 viewed
98 viewed
98 shared
59 viewed
78 viewed
38 viewed
38 shared
28 shared
17 viewed
53 shared
82 shared
35 viewed
10 viewed
76 viewed
66 shared
61 shared
70 viewed
70 shared
7 viewed
68 viewed
68 shared
4 viewed
87 shared
91 viewed
91 shared
26 viewed
26 shared
93 viewed
8 viewed
60 viewed
11 viewed
11 shared
27 viewed
31 viewed
6 viewed
6 shared
39 viewed
48 shared
15 viewed
80 viewed
80 shared
29 viewed
52 viewed
54 viewed & shared
37 shared
39 viewed
1 shared
18 viewed
18 shared
83 viewed
5 viewed
97 shared
71 shared
34 shared
57 viewed
57 shared
51 shared
99 viewed
99 shared
22 viewed
56 viewed
69 viewed
32 viewed
33 viewed
73 viewed
73 shared
75 viewed
13 viewed
13 shared
9 viewed
9 shared
25 viewed
94 viewed
98 viewed
98 shared
84 viewed
59 viewed
78 viewed
96 shared
2 viewed
74 viewed
74 shared
44 viewed
36 viewed
79 shared
16 viewed
67 viewed
20 viewed
52 viewed
52 shared
17 viewed
53 shared
82 shared
19 viewed
38 viewed
38 shared
28 shared
64 viewed
64 shared
80 viewed
80 shared
7 viewed
68 viewed
68 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
35 viewed
10 viewed
76 viewed
66 viewed
66 shared
61 shared
70 viewed
70 shared
62 viewed
62 shared
86 viewed
48 shared
8 viewed
81 shared
55 viewed
60 viewed
11 viewed
11 shared
27 viewed
26 viewed
26 shared
50 viewed
50 shared
6 viewed
6 shared
29 viewed
15 viewed
82 viewed & shared
96 shared
4 viewed
4 shared
38 viewed
38 shared
87 shared
91 viewed
91 shared
28 shared
14 shared
17 viewed
51 shared
31 viewed
81 shared
59 viewed
35 viewed
69 viewed
74 viewed
74 shared
10 viewed
76 viewed
66 viewed
66 shared
61 shared
2 viewed
55 viewed
60 viewed
11 viewed
11 shared
49 shared
27 viewed
19 viewed
70 viewed
70 shared
7 viewed
7 shared
97 shared
30 shared
46 viewed
46 shared
13 viewed
13 shared
94 viewed
29 viewed
1 shared
44 viewed
18 viewed
18 shared
56 viewed
84 viewed
36 viewed
20 viewed
26 viewed
26 shared
50 viewed
50 shared
23 viewed
39 viewed
42 viewed
93 viewed
83 viewed
52 viewed
52 shared
6 viewed
6 shared
32 viewed
32 shared
33 viewed
37 shared
65 viewed
65 shared
73 viewed
73 shared
75 viewed
9 viewed
9 shared
25 viewed
68 viewed
68 shared
88 viewed
88 shared
16 viewed
67 viewed
57 viewed
57 shared
71 shared
99 viewed
99 shared
22 viewed
62 shared
80 viewed
80 shared
48 shared
86 viewed
15 viewed
34 shared
79 shared
5 viewed
5 shared
54 viewed
78 viewed
8 viewed
53 shared
98 viewed
98 shared
64 viewed
64 shared
16 viewed & shared
48 shared
13 viewed
13 shared
69 viewed
80 viewed
80 shared
5 viewed
5 shared
6 viewed
6 shared
29 viewed
67 viewed
20 viewed
97 shared
9 viewed
2 viewed
83 viewed
52 viewed
52 shared
39 viewed
41 viewed
78 viewed
73 viewed
73 shared
37 shared
36 viewed
86 viewed
7 viewed
7 shared
26 viewed
26 shared
75 viewed
15 viewed
32 viewed
32 shared
33 viewed
65 viewed
65 shared
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18 shared
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1 shared
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71 shared
34 shared
28 shared
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19 shared
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50 shared
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70 shared
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57 shared
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62 viewed
62 shared
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98 shared
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4 shared
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91 shared
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68 viewed
68 shared
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11 shared
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70 viewed
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18 shared
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44 viewed
79 shared
97 shared
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56 viewed
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51 shared
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64 shared
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73 shared
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13 shared
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9 shared
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1 shared
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5 viewed
54 viewed
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34 shared
96 shared
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74 shared
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62 shared
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52 shared
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98 shared
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17 viewed
82 shared
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38 shared
28 shared
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80 shared
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4 shared
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91 shared
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66 shared
61 shared
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70 shared
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68 shared
81 shared
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11 viewed
11 shared
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26 viewed
26 shared
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6 shared
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8 viewed
15 viewed
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57 shared
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1 shared
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98 shared
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64 shared
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50 shared
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4 shared
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38 shared
87 shared
91 viewed
91 shared
28 shared
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44 viewed
2 viewed
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74 shared
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80 shared
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53 shared
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6 viewed
6 shared
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61 shared
81 shared
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10 viewed
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66 viewed
66 shared
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11 shared
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70 shared
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68 shared
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62 shared
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6 viewed
6 shared
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70 shared
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66 shared
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38 shared
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64 shared
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7 shared
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5 shared
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4 shared
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99 shared
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13 shared
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11 shared
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18 shared
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71 shared
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57 shared
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98 shared
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68 shared
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26 shared
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50 shared
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66 shared
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38 shared
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6 shared
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91 shared
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16 shared
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80 shared
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81 shared
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99 shared
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98 shared
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73 shared
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9 shared
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3 viewed
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53 shared
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64 shared
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68 shared
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80 shared
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11 viewed
11 shared
12 viewed
30 shared
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95 shared
48 shared
2 viewed
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52 viewed
52 shared
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41 viewed
78 viewed
91 viewed
91 shared
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68 shared
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88 shared
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73 shared
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4 shared
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16 shared
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5 shared
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6 shared
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9 shared
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13 shared
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81 shared
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67 viewed
37 shared
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26 shared
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38 shared
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28 shared
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98 shared
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1 shared
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18 shared
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34 shared
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19 shared
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70 shared
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51 shared
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74 shared
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66 shared
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57 shared
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99 shared
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32 viewed
32 shared
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62 shared
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44 viewed
79 shared
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64 shared
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65 shared
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4 shared
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38 shared
87 shared
91 viewed
91 shared
28 shared
14 shared
17 viewed
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81 shared
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74 shared
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66 viewed
66 shared
61 shared
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11 viewed
11 shared
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70 shared
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7 shared
97 shared
30 shared
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46 shared
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13 shared
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29 viewed
1 shared
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18 shared
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84 viewed
36 viewed
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26 viewed
26 shared
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50 shared
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42 viewed
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83 viewed
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52 shared
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6 shared
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32 shared
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65 shared
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73 shared
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9 shared
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68 shared
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88 shared
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57 shared
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99 shared
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80 shared
48 shared
86 viewed
15 viewed
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79 shared
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5 shared
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8 viewed
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98 shared
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64 shared
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83 viewed
53 shared
30 shared
98 viewed
98 shared
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88 shared
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73 shared
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71 shared
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32 shared
1 shared
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37 shared
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34 shared
57 viewed
27 viewed
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51 shared
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18 shared
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64 shared
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99 shared
96 shared
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74 shared
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62 viewed
62 shared
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3 viewed
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82 shared
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38 viewed
38 shared
20 viewed
28 shared
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55 viewed
4 viewed
4 shared
87 shared
91 viewed
91 shared
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10 viewed
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66 viewed
66 shared
61 shared
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70 shared
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7 shared
81 shared
60 viewed
11 viewed
11 shared
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26 shared
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52 viewed
52 shared
6 viewed
6 shared
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80 viewed
80 shared
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48 shared
75 viewed
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16 viewed
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81 shared
3 viewed
36 viewed
71 shared
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56 viewed
4 viewed
32 viewed
1 shared
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98 shared
37 shared
59 viewed
51 shared
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53 shared
18 viewed
83 viewed
5 viewed
54 viewed
97 shared
34 shared
96 shared
2 viewed
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74 shared
44 viewed
68 viewed
68 shared
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73 viewed
73 shared
75 viewed
13 viewed
13 shared
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25 viewed
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78 viewed
82 shared
38 viewed
38 shared
20 viewed
28 shared
8 viewed
30 shared
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87 shared
91 viewed
91 shared
35 viewed
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10 viewed
76 viewed
66 shared
61 shared
70 viewed
70 shared
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88 shared
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60 viewed
11 viewed
11 shared
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31 viewed
26 viewed
26 shared
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50 shared
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39 viewed
6 viewed
6 shared
48 shared
86 viewed
15 viewed
80 viewed
80 shared
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78 viewed & shared
80 viewed
80 shared
9 viewed
34 shared
88 viewed
88 shared
2 viewed
52 viewed
39 viewed
48 viewed & shared
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16 shared
80 viewed
80 shared
5 viewed
6 viewed
6 shared
29 viewed
13 shared
69 viewed
2 viewed
52 viewed
39 viewed
78 viewed
36 viewed
86 viewed
7 viewed
26 viewed
26 shared
75 viewed
15 viewed
67 viewed
20 viewed
19 viewed
50 viewed
50 shared
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70 shared
61 shared
60 viewed
28 shared
93 viewed
66 viewed
66 shared
38 viewed
38 shared
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74 shared
82 shared
35 viewed
10 viewed
76 viewed
51 shared
96 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
1 shared
44 viewed
18 viewed
18 shared
17 viewed
81 shared
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55 viewed
11 viewed
11 shared
27 viewed
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57 shared
37 shared
71 shared
99 viewed
99 shared
22 viewed
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54 viewed
34 shared
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98 shared
79 shared
53 shared
64 viewed
64 shared
68 viewed
68 shared
8 viewed
30 shared
25 viewed
88 viewed
88 shared
73 viewed
73 shared
76 viewed & shared
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65 shared
87 shared
40 shared
25 viewed
27 viewed
62 viewed
62 shared
31 viewed
97 shared
2 viewed
10 viewed
59 viewed
60 viewed
82 shared
8 viewed
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64 shared
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50 shared
3 viewed
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32 shared
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37 shared
73 viewed
73 shared
75 viewed
13 viewed
13 shared
14 shared
18 viewed
18 shared
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9 shared
94 viewed
96 shared
4 viewed
4 shared
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38 shared
91 viewed
91 shared
28 shared
86 viewed
79 shared
26 viewed
26 shared
61 shared
34 shared
71 shared
57 viewed
57 shared
1 shared
83 viewed
5 viewed
5 shared
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67 viewed
20 viewed
46 viewed
46 shared
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99 shared
22 viewed
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69 viewed
51 shared
52 viewed
52 shared
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17 viewed
81 shared
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74 shared
76 viewed
66 viewed
66 shared
11 viewed
11 shared
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19 viewed
70 viewed
70 shared
7 viewed
7 shared
6 viewed
6 shared
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98 shared
84 viewed
48 shared
36 viewed
44 viewed
80 viewed
80 shared
39 viewed
42 viewed
15 viewed
53 shared
68 viewed
68 shared
76 viewed & shared
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82 shared
35 viewed
69 viewed
12 viewed
74 viewed
74 shared
10 viewed
76 viewed
66 viewed
66 shared
61 shared
96 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
28 shared
14 shared
51 viewed
51 shared
19 viewed
19 shared
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20 viewed
20 shared
26 viewed
26 shared
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50 shared
23 viewed
17 viewed
31 viewed
81 shared
59 viewed
2 viewed
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60 viewed
11 viewed
11 shared
49 shared
27 viewed
70 viewed
70 shared
7 viewed
7 shared
97 shared
30 shared
46 viewed
46 shared
13 viewed
13 shared
94 viewed
29 viewed
1 shared
44 viewed
18 viewed
18 shared
41 viewed
93 viewed
83 viewed
6 viewed
6 shared
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62 shared
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84 viewed
39 viewed
42 viewed
52 viewed
52 shared
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32 shared
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37 shared
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65 shared
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73 shared
75 viewed
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9 shared
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68 shared
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88 shared
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67 viewed
57 viewed
57 shared
71 shared
99 viewed
99 shared
22 viewed
48 shared
86 viewed
15 viewed
64 viewed
64 shared
3 viewed
3 shared
80 viewed
80 shared
34 shared
79 shared
5 viewed
5 shared
54 viewed
78 viewed
8 viewed
53 shared
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98 shared
15 viewed & shared
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6 viewed
6 shared
48 shared
36 viewed
86 viewed
7 viewed
7 shared
26 viewed
26 shared
16 viewed
16 shared
80 viewed
80 shared
5 viewed
5 shared
28 shared
52 viewed
52 shared
19 viewed
19 shared
50 viewed
50 shared
70 viewed
70 shared
61 shared
13 viewed
13 shared
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2 viewed
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41 viewed
78 viewed
73 viewed
73 shared
67 viewed
37 shared
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74 shared
82 shared
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9 shared
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62 viewed
62 shared
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93 viewed
66 viewed
66 shared
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38 shared
23 viewed
20 viewed
97 shared
1 shared
18 viewed
18 shared
54 viewed
71 shared
34 shared
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51 shared
96 shared
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4 shared
87 shared
91 viewed
91 shared
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64 shared
65 viewed
65 shared
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3 shared
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35 viewed
12 viewed
10 viewed
76 viewed
32 viewed
32 shared
33 viewed
25 viewed
94 viewed
57 viewed
57 shared
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99 shared
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98 viewed
98 shared
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44 viewed
17 viewed
31 viewed
81 shared
11 viewed
11 shared
49 shared
27 viewed
79 shared
53 shared
68 viewed
68 shared
8 viewed
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80 shared
9 viewed
9 shared
34 shared
88 viewed
88 shared
48 shared
2 viewed
83 viewed
52 viewed
52 shared
39 viewed
41 viewed
97 shared
13 viewed
13 shared
32 viewed
16 viewed
16 shared
5 viewed
5 shared
6 viewed
6 shared
7 viewed
33 viewed
65 viewed
65 shared
73 viewed
73 shared
75 viewed
14 shared
18 viewed
18 shared
25 viewed
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20 viewed
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36 viewed
86 viewed
26 viewed
26 shared
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62 shared
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82 shared
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46 shared
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99 shared
22 viewed
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51 viewed
51 shared
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19 shared
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50 shared
70 viewed
70 shared
61 shared
64 viewed
64 shared
3 viewed
3 shared
96 shared
4 viewed
4 shared
38 viewed
38 shared
87 shared
91 viewed
91 shared
28 shared
44 viewed
79 shared
1 shared
74 viewed
74 shared
60 viewed
42 viewed
93 viewed
66 viewed
66 shared
23 viewed
35 viewed
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57 shared
17 viewed
31 viewed
81 shared
12 viewed
10 viewed
76 viewed
11 viewed
11 shared
49 shared
27 viewed
71 shared
98 viewed
98 shared
53 shared
68 viewed
68 shared
8 viewed
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68 viewed
68 shared
98 viewed
98 shared
8 viewed
41 viewed
83 viewed
30 shared
17 viewed
71 shared
25 viewed
88 viewed
88 shared
73 viewed
73 shared
14 shared
32 viewed
32 shared
1 shared
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37 shared
59 viewed
82 shared
46 viewed
46 shared
13 viewed
13 shared
94 viewed
34 shared
57 viewed
57 shared
27 viewed
79 shared
23 viewed
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51 shared
18 viewed
18 shared
54 viewed
96 shared
4 viewed
4 shared
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38 shared
87 shared
91 viewed
91 shared
28 shared
16 viewed
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20 viewed
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64 viewed
64 shared
99 viewed
99 shared
2 viewed
74 viewed
74 shared
44 viewed
22 viewed
69 viewed
31 viewed
81 shared
35 viewed
10 viewed
76 viewed
66 viewed
66 shared
61 shared
55 viewed
60 viewed
11 viewed
11 shared
49 shared
19 viewed
19 shared
70 viewed
70 shared
7 viewed
7 shared
62 viewed
62 shared
86 viewed
36 viewed
26 viewed
26 shared
50 viewed
50 shared
39 viewed
42 viewed
52 viewed
52 shared
6 viewed
6 shared
65 viewed
65 shared
80 viewed
80 shared
48 shared
75 viewed
15 viewed
5 viewed & shared
48 shared
73 viewed
73 shared
67 viewed
37 shared
16 viewed
16 shared
80 viewed
80 shared
6 viewed
6 shared
29 viewed
1 shared
18 viewed
18 shared
83 viewed
54 viewed
71 shared
34 shared
13 viewed
13 shared
69 viewed
2 viewed
52 viewed
52 shared
39 viewed
78 viewed
36 viewed
86 viewed
7 viewed
7 shared
26 viewed
26 shared
75 viewed
15 viewed
57 viewed
57 shared
51 shared
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99 shared
22 viewed
56 viewed
32 viewed
32 shared
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98 shared
59 viewed
20 viewed
9 viewed
28 shared
19 viewed
50 viewed
50 shared
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70 shared
61 shared
96 shared
74 viewed
74 shared
44 viewed
79 shared
27 viewed
17 viewed
53 shared
82 shared
60 viewed
62 shared
42 viewed
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66 shared
38 viewed
38 shared
64 viewed
64 shared
68 viewed
68 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
55 viewed
35 viewed
10 viewed
76 viewed
8 viewed
81 shared
11 viewed
11 shared
13 viewed & shared
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67 viewed
20 viewed
97 shared
9 viewed
32 viewed
32 shared
33 viewed
37 shared
65 viewed
65 shared
73 viewed
73 shared
75 viewed
18 viewed
18 shared
25 viewed
94 viewed
34 shared
71 shared
57 viewed
57 shared
27 viewed
79 shared
1 shared
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5 shared
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62 viewed
62 shared
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99 shared
22 viewed
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51 shared
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98 viewed
98 shared
84 viewed
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64 viewed
64 shared
23 viewed
48 shared
50 viewed
50 shared
36 viewed
44 viewed
96 shared
2 viewed
74 viewed
74 shared
17 viewed
53 shared
86 viewed
80 viewed
80 shared
6 viewed
6 shared
29 viewed
26 shared
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61 shared
82 shared
19 viewed
38 viewed
38 shared
28 shared
68 viewed
68 shared
52 viewed
52 shared
39 viewed
7 viewed
7 shared
15 viewed
70 viewed
70 shared
66 viewed
66 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
35 viewed
10 viewed
76 viewed
8 viewed
81 shared
11 viewed
11 shared
70 viewed & shared
26 viewed
26 shared
28 shared
42 viewed
93 viewed
19 viewed
50 viewed
50 shared
83 viewed
6 viewed
6 shared
61 shared
74 viewed
74 shared
82 shared
7 viewed
7 shared
60 viewed
62 shared
48 shared
36 viewed
86 viewed
75 viewed
15 viewed
66 viewed
66 shared
38 viewed
38 shared
23 viewed
51 shared
20 viewed
96 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
14 shared
52 viewed
52 shared
64 viewed
64 shared
65 viewed
65 shared
3 viewed
55 viewed
16 viewed
16 shared
80 viewed
80 shared
5 viewed
5 shared
29 viewed
35 viewed
69 viewed
10 viewed
76 viewed
1 shared
2 viewed
44 viewed
18 viewed
18 shared
17 viewed
31 viewed
81 shared
59 viewed
11 viewed
11 shared
49 shared
27 viewed
97 shared
30 shared
46 viewed
46 shared
13 viewed
13 shared
94 viewed
9 viewed
79 shared
39 viewed
78 viewed
73 viewed
73 shared
67 viewed
37 shared
57 viewed
57 shared
71 shared
99 viewed
99 shared
22 viewed
56 viewed
32 viewed
32 shared
33 viewed
25 viewed
68 viewed
68 shared
88 viewed
88 shared
54 viewed
34 shared
98 viewed
98 shared
8 viewed
53 shared
91 viewed & shared
17 viewed
82 shared
11 viewed
11 shared
27 viewed
60 viewed
31 viewed
96 shared
4 viewed
4 shared
38 viewed
38 shared
87 shared
28 shared
14 shared
39 viewed
2 viewed
51 shared
81 shared
59 viewed
35 viewed
69 viewed
74 viewed
74 shared
10 viewed
76 viewed
66 viewed
66 shared
61 shared
55 viewed
19 viewed
70 viewed
70 shared
7 viewed
7 shared
97 shared
30 shared
46 viewed
46 shared
13 viewed
13 shared
94 viewed
29 viewed
1 shared
44 viewed
18 viewed
18 shared
56 viewed
36 viewed
20 viewed
26 viewed
26 shared
50 viewed
50 shared
93 viewed
83 viewed
52 viewed
52 shared
6 viewed
6 shared
32 viewed
32 shared
33 viewed
37 shared
65 viewed
65 shared
73 viewed
73 shared
75 viewed
9 viewed
9 shared
25 viewed
68 viewed
68 shared
88 viewed
88 shared
16 viewed
67 viewed
57 viewed
57 shared
71 shared
99 viewed
99 shared
22 viewed
80 viewed
80 shared
48 shared
86 viewed
15 viewed
34 shared
79 shared
5 viewed
54 viewed
78 viewed
8 viewed
53 shared
98 viewed
98 shared
64 viewed
64 shared
42 viewed & shared
0 shared
90 shared
70 viewed
70 shared
13 viewed
13 shared
34 shared
69 viewed
29 viewed
26 viewed
26 shared
28 shared
93 viewed
16 viewed
67 viewed
20 viewed
97 shared
9 viewed
32 viewed
78 viewed
19 viewed
19 shared
50 viewed
50 shared
83 viewed
6 viewed
6 shared
61 shared
74 viewed
74 shared
82 shared
7 viewed
7 shared
33 viewed
65 viewed
65 shared
73 viewed
73 shared
75 viewed
18 viewed
18 shared
25 viewed
94 viewed
41 viewed
60 viewed
62 viewed
62 shared
48 shared
36 viewed
86 viewed
15 viewed
66 viewed
66 shared
38 viewed
38 shared
23 viewed
51 shared
96 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
52 viewed
52 shared
55 viewed
99 viewed
99 shared
22 viewed
56 viewed
64 viewed
64 shared
3 viewed
80 viewed
80 shared
35 viewed
10 viewed
76 viewed
1 shared
2 viewed
44 viewed
17 viewed
31 viewed
81 shared
59 viewed
11 viewed
11 shared
49 shared
27 viewed
79 shared
39 viewed
57 viewed
57 shared
71 shared
84 viewed
98 viewed
98 shared
53 shared
68 viewed
68 shared
8 viewed
74 viewed & shared
51 shared
19 viewed
36 viewed
38 viewed
38 shared
20 viewed
28 shared
96 shared
1 shared
2 viewed
44 viewed
18 viewed
18 shared
82 shared
35 viewed
69 viewed
10 viewed
76 viewed
66 viewed
66 shared
61 shared
70 viewed
70 shared
7 viewed
7 shared
17 viewed
57 viewed
37 shared
71 shared
97 shared
99 viewed
99 shared
22 viewed
56 viewed
4 viewed
87 shared
91 viewed
91 shared
26 viewed
26 shared
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50 shared
93 viewed
83 viewed
52 viewed
52 shared
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6 shared
5 viewed
54 viewed
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32 viewed
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98 shared
59 viewed
33 viewed
73 viewed
73 shared
75 viewed
13 viewed
13 shared
9 viewed
25 viewed
94 viewed
3 viewed
79 shared
55 viewed
11 viewed
11 shared
27 viewed
31 viewed
80 viewed
80 shared
48 shared
86 viewed
78 viewed
53 shared
16 viewed
67 viewed
64 viewed
64 shared
39 viewed
29 viewed
68 viewed
68 shared
8 viewed
71 viewed & shared
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32 shared
1 shared
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98 shared
84 viewed
37 shared
59 viewed
97 shared
34 shared
57 viewed
57 shared
27 viewed
79 shared
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51 shared
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53 shared
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18 shared
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5 viewed
5 shared
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33 viewed
65 viewed
65 shared
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73 shared
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13 viewed
13 shared
14 shared
9 viewed
9 shared
25 viewed
94 viewed
78 viewed
64 viewed
64 shared
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99 shared
96 shared
2 viewed
74 viewed
74 shared
44 viewed
68 viewed
68 shared
22 viewed
69 viewed
48 shared
67 viewed
62 viewed
62 shared
55 viewed
16 viewed
20 viewed
82 shared
46 viewed
46 shared
29 viewed
52 viewed
52 shared
86 viewed
36 viewed
19 viewed
19 shared
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38 shared
28 shared
8 viewed
80 viewed
80 shared
6 viewed
6 shared
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50 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
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26 viewed
26 shared
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12 viewed
10 viewed
76 viewed
66 viewed
66 shared
61 shared
70 viewed
70 shared
39 viewed
15 viewed
60 viewed
31 viewed
81 shared
11 viewed
11 shared
49 shared
42 viewed
27 viewed & shared
32 viewed
20 viewed
86 viewed
55 viewed
91 viewed
91 shared
17 viewed
82 shared
11 viewed
11 shared
60 viewed
31 viewed
96 shared
4 viewed
4 shared
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38 shared
87 shared
28 shared
39 viewed
81 shared
59 viewed
35 viewed
69 viewed
74 viewed
74 shared
10 viewed
76 viewed
66 shared
61 shared
19 viewed
70 viewed
70 shared
7 viewed
56 viewed
36 viewed
26 viewed
26 shared
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50 shared
93 viewed
83 viewed
6 viewed
6 shared
48 shared
75 viewed
15 viewed
16 viewed
16 shared
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80 shared
5 viewed
29 viewed
52 viewed
78 viewed
45 viewed & shared
48 shared
17 viewed
64 viewed
64 shared
25 viewed
16 viewed
80 viewed
80 shared
5 viewed
6 viewed
6 shared
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62 viewed
62 shared
86 viewed
79 shared
2 viewed
52 viewed
39 viewed
78 viewed
36 viewed
7 viewed
26 viewed
26 shared
75 viewed
15 viewed
50 viewed
3 viewed
55 viewed
32 viewed
99 viewed
99 shared
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70 viewed
70 shared
61 shared
18 viewed
18 shared
44 viewed
28 shared
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66 shared
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38 shared
97 shared
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56 viewed
37 shared
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51 shared
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74 shared
82 shared
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20 viewed
10 viewed
76 viewed
33 viewed
73 viewed
73 shared
13 viewed
13 shared
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94 viewed
1 shared
54 viewed
71 shared
34 shared
96 shared
4 viewed
87 shared
91 viewed
91 shared
67 viewed
57 viewed
98 viewed
98 shared
59 viewed
11 viewed
11 shared
27 viewed
31 viewed
53 shared
68 viewed
68 shared
8 viewed
56 viewed & shared
81 shared
18 viewed
18 shared
35 viewed
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57 viewed
57 shared
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95 shared
4 viewed
4 shared
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97 shared
99 viewed
99 shared
22 viewed
37 shared
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51 shared
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80 shared
36 viewed
11 viewed
11 shared
82 shared
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33 viewed
65 viewed
65 shared
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73 shared
75 viewed
13 viewed
13 shared
14 shared
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9 shared
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94 viewed
44 viewed
79 shared
83 viewed
5 viewed
5 shared
54 viewed
71 shared
34 shared
96 shared
2 viewed
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74 shared
48 shared
52 viewed
52 shared
39 viewed
78 viewed
91 viewed
38 viewed
38 shared
87 shared
28 shared
62 viewed
62 shared
55 viewed
16 viewed
67 viewed
20 viewed
46 viewed
46 shared
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64 shared
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98 shared
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19 viewed
6 viewed
6 shared
7 viewed
10 viewed
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66 viewed
66 shared
61 shared
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70 viewed
70 shared
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50 shared
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53 shared
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26 shared
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68 shared
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18 shared
3 viewed
3 shared
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44 viewed
79 shared
97 shared
22 viewed
56 viewed
37 shared
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51 viewed
51 shared
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84 viewed
57 viewed
57 shared
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62 shared
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32 shared
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64 shared
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65 shared
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73 shared
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13 shared
14 shared
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9 shared
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25 shared
94 viewed
1 shared
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5 viewed
5 shared
54 viewed
71 shared
34 shared
96 shared
2 viewed
74 viewed
74 shared
50 viewed
50 shared
55 viewed
27 viewed
86 viewed
16 viewed
67 viewed
20 viewed
82 shared
46 viewed
46 shared
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29 viewed
52 viewed
52 shared
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23 viewed
48 shared
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98 shared
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19 viewed
19 shared
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38 shared
28 shared
26 viewed
26 shared
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61 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
80 viewed
80 shared
7 viewed
7 shared
6 viewed
6 shared
53 shared
12 viewed
10 viewed
76 viewed
66 viewed
66 shared
70 viewed
70 shared
31 viewed
81 shared
11 viewed
11 shared
49 shared
39 viewed
15 viewed
68 viewed
68 shared
42 viewed
8 viewed
56 viewed & shared
81 shared
18 viewed
18 shared
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23 viewed
57 viewed
57 shared
29 viewed
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95 shared
4 viewed
4 shared
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97 shared
99 viewed
99 shared
22 viewed
37 shared
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51 viewed
51 shared
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80 shared
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11 viewed
11 shared
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82 shared
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33 viewed
65 viewed
65 shared
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73 shared
75 viewed
13 viewed
13 shared
14 shared
9 viewed
9 shared
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94 viewed
44 viewed
79 shared
83 viewed
5 viewed
5 shared
54 viewed
71 shared
34 shared
96 shared
2 viewed
74 viewed
74 shared
48 shared
52 viewed
52 shared
39 viewed
41 viewed
78 viewed
91 viewed
91 shared
38 viewed
38 shared
87 shared
28 shared
62 viewed
62 shared
55 viewed
16 viewed
67 viewed
20 viewed
46 viewed
46 shared
64 viewed
64 shared
98 viewed
98 shared
17 viewed
19 viewed
19 shared
6 viewed
6 shared
7 viewed
27 viewed
60 viewed
12 viewed
10 viewed
76 viewed
66 viewed
66 shared
61 shared
70 viewed
70 shared
50 viewed
50 shared
86 viewed
53 shared
26 viewed
26 shared
15 viewed
42 viewed
68 viewed
68 shared
8 viewed
78 viewed & shared
80 viewed
80 shared
9 viewed
9 shared
34 shared
88 viewed
88 shared
48 shared
2 viewed
83 viewed
52 viewed
52 shared
39 viewed
97 shared
13 viewed
13 shared
32 viewed
16 viewed
16 shared
5 viewed
5 shared
6 viewed
6 shared
7 viewed
33 viewed
65 viewed
65 shared
73 viewed
73 shared
75 viewed
18 viewed
18 shared
25 viewed
94 viewed
67 viewed
20 viewed
69 viewed
36 viewed
86 viewed
26 viewed
26 shared
15 viewed
62 viewed
62 shared
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99 shared
22 viewed
56 viewed
51 shared
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50 viewed
50 shared
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70 shared
61 shared
64 viewed
64 shared
3 viewed
44 viewed
79 shared
96 shared
1 shared
74 viewed
74 shared
60 viewed
28 shared
93 viewed
66 viewed
66 shared
38 viewed
38 shared
17 viewed
82 shared
57 viewed
57 shared
71 shared
35 viewed
10 viewed
76 viewed
4 viewed
4 shared
87 shared
91 viewed
91 shared
98 viewed
98 shared
59 viewed
81 shared
11 viewed
11 shared
27 viewed
53 shared
68 viewed
68 shared
8 viewed
72 viewed & shared
43 viewed
43 shared
13 viewed
13 shared
94 viewed
16 viewed
67 viewed
20 viewed
97 shared
9 viewed
32 viewed
32 shared
33 viewed
37 shared
65 viewed
65 shared
73 viewed
73 shared
75 viewed
18 viewed
18 shared
25 viewed
34 shared
71 shared
57 viewed
57 shared
27 viewed
79 shared
1 shared
83 viewed
5 viewed
5 shared
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62 viewed
62 shared
55 viewed
99 viewed
99 shared
22 viewed
56 viewed
69 viewed
51 shared
78 viewed
98 viewed
98 shared
84 viewed
59 viewed
64 viewed
64 shared
48 shared
50 viewed
50 shared
36 viewed
44 viewed
96 shared
2 viewed
74 viewed
74 shared
17 viewed
53 shared
86 viewed
80 viewed
80 shared
6 viewed
6 shared
29 viewed
26 shared
60 viewed
61 shared
82 shared
19 viewed
38 viewed
38 shared
28 shared
68 viewed
68 shared
52 viewed
52 shared
39 viewed
7 viewed
7 shared
15 viewed
70 viewed
70 shared
66 viewed
66 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
35 viewed
10 viewed
76 viewed
8 viewed
42 viewed
81 shared
11 viewed
11 shared
99 viewed & shared
18 viewed
18 shared
3 viewed
3 shared
36 viewed
44 viewed
79 shared
97 shared
22 viewed
56 viewed
37 shared
69 viewed
51 viewed
51 shared
35 viewed
84 viewed
57 viewed
57 shared
62 viewed
62 shared
32 viewed
32 shared
64 viewed
64 shared
33 viewed
65 viewed
65 shared
73 viewed
73 shared
75 viewed
13 viewed
13 shared
14 shared
9 viewed
9 shared
25 viewed
94 viewed
1 shared
83 viewed
5 viewed
5 shared
54 viewed
71 shared
34 shared
96 shared
2 viewed
74 viewed
74 shared
50 viewed
50 shared
55 viewed
27 viewed
86 viewed
16 viewed
67 viewed
20 viewed
82 shared
46 viewed
46 shared
59 viewed
29 viewed
52 viewed
52 shared
78 viewed
23 viewed
48 shared
98 viewed
98 shared
17 viewed
19 viewed
19 shared
38 viewed
38 shared
28 shared
26 viewed
26 shared
60 viewed
61 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
80 viewed
80 shared
7 viewed
6 viewed
6 shared
53 shared
12 viewed
10 viewed
76 viewed
66 viewed
66 shared
70 viewed
70 shared
31 viewed
81 shared
11 viewed
11 shared
49 shared
39 viewed
15 viewed
68 viewed
68 shared
42 viewed
8 viewed
5 viewed & shared
48 shared
73 viewed
73 shared
67 viewed
37 shared
16 viewed
16 shared
80 viewed
80 shared
6 viewed
6 shared
29 viewed
1 shared
18 viewed
18 shared
83 viewed
54 viewed
71 shared
34 shared
13 viewed
13 shared
69 viewed
2 viewed
52 viewed
52 shared
39 viewed
78 viewed
36 viewed
86 viewed
7 viewed
7 shared
26 viewed
26 shared
75 viewed
15 viewed
23 viewed
57 viewed
57 shared
51 shared
99 viewed
99 shared
22 viewed
56 viewed
32 viewed
32 shared
98 viewed
98 shared
59 viewed
20 viewed
9 viewed
28 shared
19 viewed
50 viewed
50 shared
70 viewed
70 shared
61 shared
96 shared
74 viewed
74 shared
44 viewed
79 shared
27 viewed
17 viewed
53 shared
82 shared
60 viewed
62 shared
42 viewed
66 viewed
66 shared
38 viewed
38 shared
64 viewed
64 shared
68 viewed
68 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
65 shared
55 viewed
35 viewed
10 viewed
76 viewed
8 viewed
81 shared
11 viewed
11 shared
49 shared
17 viewed & shared
96 shared
98 viewed
98 shared
91 viewed
91 shared
82 shared
53 shared
71 shared
11 viewed
11 shared
27 viewed
60 viewed
31 viewed
4 viewed
4 shared
38 viewed
38 shared
87 shared
28 shared
68 viewed
68 shared
32 viewed
32 shared
1 shared
84 viewed
37 shared
59 viewed
39 viewed
81 shared
35 viewed
69 viewed
74 viewed
74 shared
10 viewed
76 viewed
66 viewed
66 shared
61 shared
55 viewed
19 viewed
70 viewed
70 shared
7 viewed
7 shared
8 viewed
41 viewed
83 viewed
30 shared
97 shared
34 shared
57 viewed
79 shared
18 viewed
18 shared
5 viewed
54 viewed
56 viewed
36 viewed
20 viewed
26 viewed
26 shared
50 viewed
50 shared
93 viewed
52 viewed
52 shared
6 viewed
6 shared
25 viewed
88 viewed
88 shared
73 viewed
73 shared
33 viewed
75 viewed
13 viewed
13 shared
9 viewed
9 shared
94 viewed
78 viewed
64 viewed
64 shared
99 viewed
99 shared
22 viewed
80 viewed
80 shared
48 shared
86 viewed
15 viewed
16 viewed
67 viewed
3 viewed
44 viewed
2 viewed & shared
80 viewed
80 shared
51 shared
87 shared
11 viewed
11 shared
31 viewed
48 shared
83 viewed
52 viewed
52 shared
39 viewed
78 viewed
96 shared
1 shared
74 viewed
74 shared
44 viewed
18 viewed
18 shared
55 viewed
10 viewed
59 viewed
60 viewed
82 shared
91 viewed
16 viewed
16 shared
5 viewed
5 shared
6 viewed
6 shared
29 viewed
9 viewed
7 viewed
17 viewed
57 viewed
57 shared
37 shared
71 shared
19 viewed
36 viewed
38 viewed
38 shared
20 viewed
28 shared
97 shared
99 viewed
99 shared
22 viewed
56 viewed
69 viewed
4 viewed
4 shared
14 shared
13 viewed
13 shared
73 viewed
73 shared
67 viewed
86 viewed
26 viewed
26 shared
75 viewed
15 viewed
54 viewed
34 shared
98 viewed
98 shared
35 viewed
76 viewed
66 viewed
66 shared
61 shared
70 viewed
70 shared
33 viewed
65 viewed
65 shared
25 viewed
94 viewed
79 shared
81 shared
30 shared
46 viewed
46 shared
50 viewed
50 shared
53 shared
62 viewed
62 shared
64 viewed
64 shared
68 viewed
68 shared
88 viewed
88 shared
8 viewed
39 viewed & shared
80 viewed
80 shared
11 viewed
11 shared
69 viewed
54 viewed
48 shared
2 viewed
83 viewed
52 viewed
52 shared
41 viewed
78 viewed
91 viewed
91 shared
16 viewed
16 shared
5 viewed
5 shared
6 viewed
6 shared
29 viewed
9 viewed
9 shared
7 viewed
17 viewed
82 shared
49 shared
27 viewed
60 viewed
31 viewed
13 viewed
13 shared
73 viewed
73 shared
67 viewed
37 shared
36 viewed
86 viewed
26 viewed
26 shared
75 viewed
15 viewed
97 shared
96 shared
4 viewed
4 shared
38 viewed
38 shared
87 shared
28 shared
14 shared
81 shared
20 viewed
1 shared
18 viewed
18 shared
71 shared
34 shared
19 viewed
19 shared
50 viewed
50 shared
70 viewed
70 shared
61 shared
32 viewed
32 shared
33 viewed
65 viewed
65 shared
25 viewed
94 viewed
51 shared
59 viewed
35 viewed
12 viewed
74 viewed
74 shared
10 viewed
76 viewed
66 viewed
66 shared
55 viewed
46 viewed
46 shared
56 viewed
23 viewed
57 viewed
57 shared
99 viewed
99 shared
22 viewed
98 viewed
98 shared
62 viewed
62 shared
42 viewed
93 viewed
79 shared
44 viewed
53 shared
64 viewed
64 shared
68 viewed
68 shared
8 viewed
2 viewed & shared
80 viewed
80 shared
51 shared
87 shared
11 viewed
11 shared
31 viewed
48 shared
52 viewed
39 viewed
78 viewed
96 shared
1 shared
74 viewed
74 shared
44 viewed
18 viewed
18 shared
55 viewed
10 viewed
59 viewed
60 viewed
82 shared
91 viewed
16 viewed
16 shared
5 viewed
6 viewed
6 shared
29 viewed
17 viewed
57 viewed
57 shared
37 shared
71 shared
19 viewed
36 viewed
38 viewed
38 shared
20 viewed
28 shared
97 shared
99 viewed
99 shared
22 viewed
56 viewed
69 viewed
4 viewed
4 shared
13 shared
86 viewed
7 viewed
26 viewed
26 shared
75 viewed
15 viewed
54 viewed
34 shared
98 viewed
98 shared
35 viewed
76 viewed
66 viewed
66 shared
61 shared
70 viewed
70 shared
33 viewed
73 viewed
73 shared
9 viewed
9 shared
25 viewed
94 viewed
79 shared
81 shared
67 viewed
50 viewed
50 shared
53 shared
64 viewed
64 shared
68 viewed
68 shared
8 viewed
52 viewed & shared
80 viewed
80 shared
9 viewed
9 shared
7 viewed
48 shared
2 viewed
83 viewed
39 viewed
41 viewed
78 viewed
97 shared
13 viewed
13 shared
16 viewed
16 shared
5 viewed
5 shared
6 viewed
6 shared
29 viewed
32 viewed
32 shared
33 viewed
37 shared
65 viewed
65 shared
73 viewed
73 shared
75 viewed
14 shared
18 viewed
18 shared
25 viewed
94 viewed
67 viewed
20 viewed
69 viewed
36 viewed
86 viewed
26 viewed
26 shared
15 viewed
34 shared
71 shared
57 viewed
57 shared
27 viewed
79 shared
1 shared
54 viewed
62 viewed
62 shared
55 viewed
82 shared
46 viewed
46 shared
59 viewed
99 viewed
99 shared
22 viewed
56 viewed
51 viewed
51 shared
19 viewed
19 shared
50 viewed
50 shared
70 viewed
70 shared
61 shared
98 viewed
98 shared
64 viewed
64 shared
23 viewed
96 shared
4 viewed
4 shared
38 viewed
38 shared
87 shared
91 viewed
91 shared
28 shared
44 viewed
74 viewed
74 shared
60 viewed
42 viewed
66 viewed
66 shared
17 viewed
53 shared
31 viewed
81 shared
35 viewed
10 viewed
76 viewed
11 viewed
11 shared
49 shared
68 viewed
68 shared
8 viewed
92 viewed & shared
27 viewed
69 viewed & shared
16 viewed
16 shared
18 viewed
18 shared
67 viewed
38 viewed
38 shared
39 viewed
31 viewed
13 shared
97 shared
99 viewed
99 shared
22 viewed
56 viewed
37 shared
51 shared
82 shared
35 viewed
74 viewed
74 shared
10 viewed
76 viewed
66 viewed
66 shared
61 shared
20 viewed
32 viewed
33 viewed
73 viewed
73 shared
75 viewed
25 viewed
94 viewed
3 viewed
36 viewed
44 viewed
79 shared
1 shared
83 viewed
5 viewed
54 viewed
71 shared
34 shared
96 shared
2 viewed
4 viewed
4 shared
87 shared
91 viewed
91 shared
28 shared
19 viewed
26 viewed
26 shared
50 viewed
50 shared
64 viewed
64 shared
57 viewed
57 shared
98 viewed
98 shared
59 viewed
78 viewed
17 viewed
81 shared
55 viewed
60 viewed
11 viewed
11 shared
27 viewed
70 viewed
70 shared
7 viewed
7 shared
6 viewed
6 shared
86 viewed
53 shared
52 viewed
52 shared
15 viewed
68 viewed
68 shared
80 viewed
80 shared
8 viewed
93 viewed & shared
12 viewed
20 viewed
20 shared
57 viewed
57 shared
70 viewed
70 shared
66 viewed
66 shared
27 viewed
74 viewed
74 shared
13 viewed
13 shared
26 viewed
26 shared
28 shared
42 viewed
35 viewed
61 shared
38 viewed
38 shared
51 viewed
51 shared
19 viewed
19 shared
36 viewed
16 viewed
67 viewed
97 shared
9 viewed
50 viewed
50 shared
83 viewed
6 viewed
6 shared
82 shared
7 viewed
7 shared
23 viewed
69 viewed
10 viewed
76 viewed
96 shared
2 viewed
44 viewed
18 viewed
18 shared
41 viewed
33 viewed
37 shared
65 viewed
65 shared
73 viewed
73 shared
75 viewed
25 viewed
94 viewed
60 viewed
62 viewed
62 shared
48 shared
86 viewed
15 viewed
4 viewed
4 shared
87 shared
91 viewed
91 shared
52 viewed
52 shared
17 viewed
99 viewed
99 shared
22 viewed
5 viewed
5 shared
54 viewed
71 shared
34 shared
55 viewed
64 viewed
64 shared
80 viewed
80 shared
29 viewed
31 viewed
81 shared
59 viewed
11 viewed
11 shared
49 shared
79 shared
98 viewed
98 shared
78 viewed
39 viewed
53 shared
68 viewed
68 shared
8 viewed
84 viewed & shared
57 viewed
33 viewed & shared
97 shared
10 viewed
60 viewed
31 viewed
32 viewed
32 shared
37 shared
65 viewed
65 shared
73 viewed
73 shared
75 viewed
13 viewed
13 shared
14 shared
18 viewed
18 shared
9 viewed
9 shared
25 viewed
94 viewed
34 shared
71 shared
57 viewed
27 viewed
79 shared
1 shared
83 viewed
5 viewed
5 shared
54 viewed
62 viewed
62 shared
55 viewed
16 viewed
67 viewed
20 viewed
82 shared
46 viewed
46 shared
59 viewed
29 viewed
99 viewed
99 shared
22 viewed
56 viewed
69 viewed
51 shared
52 viewed
52 shared
78 viewed
98 viewed
98 shared
84 viewed
64 viewed
64 shared
48 shared
50 viewed
3 viewed
96 shared
4 viewed
4 shared
38 viewed
38 shared
87 shared
91 viewed
91 shared
28 shared
36 viewed
44 viewed
2 viewed
74 viewed
74 shared
80 viewed
80 shared
7 viewed
17 viewed
53 shared
86 viewed
6 viewed
6 shared
81 shared
35 viewed
76 viewed
66 viewed
66 shared
61 shared
11 viewed
11 shared
19 viewed
70 viewed
70 shared
39 viewed
68 viewed
68 shared
26 viewed
26 shared
15 viewed
93 viewed
8 viewed
57 viewed & shared
24 viewed & shared
80 viewed
80 shared
35 viewed
8 viewed
11 viewed
11 shared
30 shared
2 viewed
52 viewed
39 viewed
78 viewed
91 viewed
68 viewed
68 shared
25 viewed
88 viewed
88 shared
73 viewed
73 shared
53 shared
98 viewed
98 shared
17 viewed
71 shared
32 viewed
1 shared
37 shared
59 viewed
57 viewed
51 shared
18 viewed
54 viewed
34 shared
96 shared
74 viewed
74 shared
44 viewed
82 shared
36 viewed
38 viewed
38 shared
20 viewed
28 shared
4 viewed
87 shared
69 viewed
10 viewed
76 viewed
66 shared
61 shared
70 viewed
70 shared
7 viewed
55 viewed
26 viewed
26 shared
50 viewed
93 viewed
6 viewed
6 shared
86 viewed
75 viewed
15 viewed
92 viewed & shared
27 viewed
44 viewed & shared
51 shared
10 viewed
99 viewed
99 shared
35 viewed
96 shared
1 shared
2 viewed
74 viewed
74 shared
18 viewed
18 shared
3 viewed
3 shared
36 viewed
79 shared
17 viewed
82 shared
23 viewed
57 viewed
57 shared
37 shared
71 shared
19 viewed
38 viewed
38 shared
20 viewed
28 shared
97 shared
22 viewed
56 viewed
69 viewed
84 viewed
62 viewed
62 shared
32 viewed
32 shared
64 viewed
64 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
14 shared
83 viewed
5 viewed
5 shared
54 viewed
34 shared
98 viewed
98 shared
59 viewed
76 viewed
66 viewed
66 shared
61 shared
70 viewed
70 shared
7 viewed
7 shared
33 viewed
65 viewed
65 shared
73 viewed
73 shared
75 viewed
13 viewed
13 shared
9 viewed
9 shared
25 viewed
94 viewed
50 viewed
50 shared
55 viewed
27 viewed
86 viewed
81 shared
60 viewed
11 viewed
11 shared
49 shared
30 shared
46 viewed
46 shared
29 viewed
48 shared
67 viewed
78 viewed
53 shared
26 viewed
26 shared
42 viewed
52 viewed
52 shared
6 viewed
6 shared
16 viewed
39 viewed
68 viewed
68 shared
88 viewed
88 shared
80 viewed
80 shared
15 viewed
8 viewed
43 viewed & shared
72 viewed
80 viewed & shared
48 shared
2 viewed
52 viewed
39 viewed
78 viewed
16 viewed
5 viewed
6 viewed
6 shared
29 viewed
36 viewed
86 viewed
7 viewed
26 viewed
26 shared
75 viewed
15 viewed
19 viewed
50 viewed
50 shared
70 viewed
70 shared
61 shared
28 shared
93 viewed
66 shared
38 viewed
38 shared
74 viewed
74 shared
82 shared
35 viewed
20 viewed
69 viewed
10 viewed
76 viewed
51 shared
96 shared
4 viewed
87 shared
91 viewed
91 shared
1 shared
44 viewed
18 viewed
55 viewed
59 viewed
11 viewed
27 viewed
57 viewed
71 shared
32 viewed
98 viewed
98 shared
53 shared
68 viewed
68 shared
8 viewed
30 shared
25 viewed
88 viewed
88 shared
73 viewed
73 shared
27 viewed & shared
32 viewed
32 shared
20 viewed
20 shared
86 viewed
55 viewed
91 viewed
91 shared
92 shared
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34 shared
71 shared
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57 shared
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66 shared
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37 shared
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1 shared
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52 shared
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26 shared
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70 shared
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7 shared
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80 shared
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68 shared
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6 shared
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8 viewed
15 viewed
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80 shared
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9 shared
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48 shared
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52 shared
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16 shared
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91 shared
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68 shared
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64 shared
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62 shared
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38 shared
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6 shared
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28 shared
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91 shared
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6 shared
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11 shared
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80 shared
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87 shared
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13 shared
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17 viewed
53 shared
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26 shared
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68 viewed
68 shared
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6 shared
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16 shared
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80 shared
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5 shared
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6 shared
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13 viewed
13 shared
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2 viewed
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52 viewed
52 shared
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73 viewed
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7 shared
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1 shared
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50 shared
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70 shared
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98 shared
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91 shared
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64 shared
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68 viewed
68 shared
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11 shared
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50 shared
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91 shared
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87 shared
26 shared
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62 shared
17 viewed
82 shared
11 viewed
11 shared
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2 viewed
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10 viewed
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83 viewed
6 viewed
6 shared
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70 shared
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66 shared
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38 shared
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64 shared
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4 shared
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14 shared
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7 viewed
7 shared
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74 viewed
74 shared
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97 shared
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13 shared
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16 shared
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80 shared
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5 shared
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52 shared
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32 shared
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99 shared
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73 viewed
73 shared
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18 shared
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9 shared
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1 shared
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68 shared
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88 shared
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98 shared
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80 shared
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9 shared
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88 shared
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52 shared
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97 shared
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13 shared
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16 shared
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18 shared
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26 shared
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62 shared
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50 shared
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64 shared
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38 shared
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91 shared
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1 shared
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66 shared
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11 viewed
11 shared
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57 shared
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68 shared
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32 shared
1 shared
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98 shared
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37 shared
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97 shared
34 shared
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57 shared
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51 shared
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18 shared
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5 shared
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65 shared
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13 shared
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9 shared
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64 shared
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99 shared
96 shared
2 viewed
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74 shared
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68 shared
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48 shared
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62 viewed
62 shared
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82 shared
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46 shared
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52 shared
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36 viewed
19 viewed
19 shared
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38 shared
28 shared
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80 shared
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6 shared
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50 shared
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4 shared
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91 viewed
91 shared
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7 shared
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26 shared
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12 viewed
10 viewed
76 viewed
66 viewed
66 shared
61 shared
70 viewed
70 shared
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31 viewed
81 shared
11 viewed
11 shared
49 shared
42 viewed
61 viewed & shared
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26 shared
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50 shared
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38 viewed
38 shared
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6 viewed
6 shared
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70 shared
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20 viewed
82 shared
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74 shared
10 viewed
76 viewed
48 shared
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86 viewed
7 viewed
75 viewed
15 viewed
28 shared
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96 shared
4 viewed
87 shared
91 viewed
91 shared
51 shared
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80 shared
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11 viewed
11 shared
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1 shared
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18 shared
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97 shared
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99 shared
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54 viewed
34 shared
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98 shared
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73 shared
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13 shared
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25 viewed
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3 viewed
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53 shared
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64 shared
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68 shared
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68 shared
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98 shared
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83 viewed
30 shared
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71 shared
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88 shared
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73 shared
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1 shared
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37 shared
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51 shared
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18 shared
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96 shared
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74 shared
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99 shared
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82 shared
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38 shared
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28 shared
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4 shared
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91 shared
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61 shared
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70 shared
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64 shared
81 shared
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11 viewed
11 shared
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26 shared
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50 shared
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62 viewed
62 shared
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6 shared
48 shared
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16 viewed
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80 shared
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64 shared
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3 viewed
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86 viewed
79 shared
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99 shared
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18 shared
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99 shared
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51 shared
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32 shared
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73 shared
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13 shared
14 shared
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9 shared
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25 shared
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3 viewed
3 shared
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1 shared
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5 shared
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34 shared
96 shared
2 viewed
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74 shared
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57 shared
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62 shared
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20 viewed
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46 shared
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52 shared
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64 shared
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98 shared
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19 shared
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38 shared
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50 shared
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4 shared
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91 shared
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80 shared
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7 shared
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6 viewed
6 shared
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26 shared
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10 viewed
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66 viewed
66 shared
61 shared
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70 shared
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81 shared
11 viewed
11 shared
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15 viewed
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68 shared
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26 viewed
26 shared
28 shared
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74 shared
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50 shared
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6 viewed
6 shared
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70 shared
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82 shared
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7 shared
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38 shared
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62 shared
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75 viewed
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66 shared
96 shared
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4 shared
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91 shared
14 shared
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52 shared
1 shared
2 viewed
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18 shared
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10 viewed
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64 shared
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16 shared
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80 shared
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5 shared
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17 viewed
81 shared
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11 viewed
11 shared
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97 shared
30 shared
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46 shared
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13 shared
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57 shared
37 shared
71 shared
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99 shared
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73 viewed
73 shared
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32 shared
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68 shared
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88 shared
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34 shared
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98 shared
8 viewed
53 shared
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66 shared
3 viewed
3 shared
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38 shared
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44 viewed
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31 viewed
20 viewed
61 shared
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99 shared
84 viewed
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57 shared
62 viewed
62 shared
82 shared
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74 shared
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26 shared
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50 shared
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18 shared
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64 shared
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96 shared
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4 shared
87 shared
91 viewed
91 shared
28 shared
51 shared
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6 shared
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70 shared
97 shared
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37 shared
86 viewed
17 viewed
81 shared
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2 viewed
11 viewed
11 shared
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7 shared
48 shared
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15 viewed
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73 viewed
73 shared
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13 shared
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9 shared
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5 viewed
5 shared
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71 shared
34 shared
39 viewed
52 viewed
52 shared
16 viewed
16 shared
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80 shared
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78 viewed
98 viewed
98 shared
53 shared
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68 shared
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43 shared
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13 shared
94 viewed
16 viewed
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20 viewed
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32 shared
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37 shared
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65 shared
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73 shared
75 viewed
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18 shared
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71 shared
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1 shared
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5 shared
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62 shared
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99 shared
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98 shared
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64 shared
48 shared
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50 shared
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96 shared
2 viewed
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74 shared
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53 shared
86 viewed
80 viewed
80 shared
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6 shared
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61 shared
82 shared
19 viewed
38 viewed
38 shared
28 shared
68 viewed
68 shared
52 viewed
52 shared
39 viewed
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7 shared
15 viewed
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66 shared
4 viewed
4 shared
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91 viewed
91 shared
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70 viewed
70 shared
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81 shared
11 viewed
11 shared
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64 shared
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99 shared
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62 shared
86 viewed
18 viewed
18 shared
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3 shared
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50 shared
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97 shared
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37 shared
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57 shared
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61 shared
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73 shared
75 viewed
13 viewed
13 shared
14 shared
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9 shared
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1 shared
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5 shared
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71 shared
34 shared
96 shared
2 viewed
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74 shared
66 viewed
66 shared
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38 shared
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20 viewed
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46 shared
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29 viewed
52 viewed
52 shared
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48 shared
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98 shared
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19 viewed
28 shared
10 viewed
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4 viewed
4 shared
87 shared
91 viewed
91 shared
80 viewed
80 shared
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6 viewed
6 shared
53 shared
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70 shared
81 shared
11 viewed
11 shared
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39 viewed
15 viewed
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68 shared
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64 shared
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3 viewed
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86 viewed
79 shared
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99 shared
18 viewed
18 shared
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97 shared
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37 shared
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51 shared
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73 shared
75 viewed
13 viewed
13 shared
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9 shared
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1 shared
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54 viewed
71 shared
34 shared
96 shared
2 viewed
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74 shared
16 viewed
67 viewed
20 viewed
52 viewed
52 shared
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57 viewed
98 viewed
98 shared
84 viewed
59 viewed
17 viewed
82 shared
19 viewed
38 viewed
38 shared
28 shared
80 viewed
80 shared
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53 shared
4 viewed
87 shared
91 viewed
91 shared
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10 viewed
76 viewed
66 shared
61 shared
70 viewed
70 shared
39 viewed
68 viewed
68 shared
60 viewed
11 viewed
11 shared
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31 viewed
26 viewed
26 shared
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8 viewed
6 viewed
6 shared
15 viewed
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1 shared
18 viewed
83 viewed
5 viewed
54 viewed
97 shared
71 shared
34 shared
57 viewed
51 shared
32 viewed
33 viewed
73 viewed
73 shared
75 viewed
13 viewed
13 shared
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9 shared
25 viewed
94 viewed
98 viewed
98 shared
84 viewed
59 viewed
78 viewed
96 shared
2 viewed
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74 shared
44 viewed
16 viewed
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20 viewed
52 viewed
52 shared
17 viewed
53 shared
82 shared
19 viewed
36 viewed
38 viewed
38 shared
28 shared
80 viewed
80 shared
7 viewed
68 viewed
68 shared
4 viewed
87 shared
91 viewed
91 shared
35 viewed
69 viewed
10 viewed
76 viewed
66 shared
61 shared
70 viewed
70 shared
39 viewed
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55 viewed
60 viewed
11 viewed
11 shared
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31 viewed
26 viewed
26 shared
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50 shared
93 viewed
6 viewed
6 shared
86 viewed
15 viewed
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80 viewed
80 shared
9 viewed
9 shared
34 shared
88 viewed
88 shared
48 shared
2 viewed
83 viewed
52 viewed
52 shared
39 viewed
41 viewed
97 shared
13 viewed
13 shared
32 viewed
37 shared
16 viewed
16 shared
5 viewed
5 shared
6 viewed
6 shared
7 viewed
7 shared
33 viewed
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65 shared
73 viewed
73 shared
75 viewed
14 shared
18 viewed
18 shared
25 viewed
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20 viewed
1 shared
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36 viewed
86 viewed
26 viewed
26 shared
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28 shared
62 viewed
62 shared
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82 shared
46 viewed
46 shared
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99 shared
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51 viewed
51 shared
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57 shared
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98 shared
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19 shared
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50 shared
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70 shared
61 shared
74 viewed
74 shared
64 viewed
64 shared
3 viewed
3 shared
96 shared
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4 shared
38 viewed
38 shared
87 shared
91 viewed
91 shared
44 viewed
79 shared
17 viewed
53 shared
60 viewed
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66 viewed
66 shared
35 viewed
31 viewed
81 shared
12 viewed
10 viewed
76 viewed
11 viewed
11 shared
49 shared
27 viewed
68 viewed
68 shared
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5 viewed & shared
48 shared
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73 shared
67 viewed
37 shared
16 viewed
16 shared
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80 shared
6 viewed
6 shared
29 viewed
1 shared
18 viewed
18 shared
83 viewed
54 viewed
71 shared
34 shared
13 shared
69 viewed
2 viewed
52 viewed
39 viewed
78 viewed
36 viewed
86 viewed
7 viewed
26 viewed
26 shared
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57 viewed
57 shared
51 shared
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99 shared
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56 viewed
32 viewed
32 shared
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98 shared
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50 viewed
50 shared
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70 shared
61 shared
96 shared
74 viewed
74 shared
44 viewed
79 shared
27 viewed
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53 shared
28 shared
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66 shared
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38 shared
82 shared
64 viewed
64 shared
68 viewed
68 shared
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10 viewed
76 viewed
4 viewed
4 shared
87 shared
91 viewed
91 shared
8 viewed
81 shared
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11 viewed
11 shared
7 viewed & shared
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83 viewed
52 viewed
52 shared
6 viewed
6 shared
74 viewed
74 shared
19 viewed
82 shared
70 viewed
70 shared
80 viewed
80 shared
9 viewed
48 shared
36 viewed
86 viewed
26 viewed
26 shared
75 viewed
15 viewed
51 shared
38 viewed
38 shared
20 viewed
96 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
93 viewed
2 viewed
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78 viewed
16 viewed
5 viewed
29 viewed
50 viewed
50 shared
61 shared
1 shared
44 viewed
18 viewed
18 shared
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10 viewed
76 viewed
66 shared
17 viewed
81 shared
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55 viewed
60 viewed
11 viewed
11 shared
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37 shared
71 shared
97 shared
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99 shared
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54 viewed
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73 shared
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13 shared
25 viewed
94 viewed
3 viewed
79 shared
53 shared
67 viewed
64 viewed
64 shared
68 viewed
68 shared
8 viewed
66 viewed & shared
35 viewed
20 viewed
61 shared
38 viewed
38 shared
26 viewed
26 shared
50 viewed
50 shared
23 viewed
82 shared
69 viewed
12 viewed
74 viewed
74 shared
10 viewed
76 viewed
19 viewed
19 shared
83 viewed
6 viewed
6 shared
70 viewed
70 shared
60 viewed
62 viewed
62 shared
96 shared
4 viewed
4 shared
87 shared
91 viewed
91 shared
28 shared
14 shared
51 viewed
51 shared
36 viewed
41 viewed
48 shared
86 viewed
7 viewed
7 shared
75 viewed
15 viewed
42 viewed
93 viewed
64 viewed
64 shared
65 viewed
65 shared
3 viewed
3 shared
55 viewed
17 viewed
31 viewed
81 shared
59 viewed
2 viewed
11 viewed
11 shared
49 shared
27 viewed
97 shared
30 shared
46 viewed
46 shared
13 viewed
13 shared
94 viewed
29 viewed
1 shared
44 viewed
18 viewed
18 shared
16 viewed
16 shared
80 viewed
80 shared
5 viewed
5 shared
52 viewed
52 shared
79 shared
99 viewed
99 shared
84 viewed
57 viewed
57 shared
56 viewed
39 viewed
32 viewed
32 shared
33 viewed
37 shared
73 viewed
73 shared
9 viewed
9 shared
25 viewed
68 viewed
68 shared
88 viewed
88 shared
67 viewed
71 shared
22 viewed
78 viewed
34 shared
54 viewed
8 viewed
53 shared
98 viewed
98 shared
13 viewed & shared
16 viewed
67 viewed
20 viewed
In [79]:
df.head(10)
Out[79]:
id
nviews
rating
nrating
iniviews
eviews
0
bG-a5ZSdO2I
21182
4.720000
418
21182
31773
1
46wXWDiigE8
13035
4.286420
486
12908
19990
2
X5h6xg7BcbQ
14543
4.553460
526
14479
22040
3
VKavlhLlZHc
1055
3.437303
89
990
1790
4
DgGZL_rAR8U
22290
4.320078
643
22158
33889
5
CIm4ci3Y6iM
19436
4.566596
805
19372
29376
6
GOrNw5IeEB8
51482
4.337150
842
51418
77436
7
LyuwSEYBAPg
528175
4.425800
3752
528111
792479
8
wzs4NzyWVB0
16073
3.928805
745
15839
24941
9
Z-ZP7Jt-RUM
16607
4.258787
544
16482
25331
In [80]:
df.tail()
Out[80]:
id
nviews
rating
nrating
iniviews
eviews
995
NWwrEEP8EBk
156875
4.38
326
156875
235312
996
pow5_UYKaJ8
157316
4.74
600
157316
235974
997
eQuIhJId1JY
265245
3.40
859
265245
397867
998
QF4CQeK91bk
25370
3.37
186
25370
38055
999
t2axP1lWFhg
125062
3.57
471
125062
187593
In [81]:
df['Expectation'] = df['eviews'] - df['nviews']
In [82]:
df.head(10)
Out[82]:
id
nviews
rating
nrating
iniviews
eviews
Expectation
0
bG-a5ZSdO2I
21182
4.720000
418
21182
31773
10591
1
46wXWDiigE8
13035
4.286420
486
12908
19990
6955
2
X5h6xg7BcbQ
14543
4.553460
526
14479
22040
7497
3
VKavlhLlZHc
1055
3.437303
89
990
1790
735
4
DgGZL_rAR8U
22290
4.320078
643
22158
33889
11599
5
CIm4ci3Y6iM
19436
4.566596
805
19372
29376
9940
6
GOrNw5IeEB8
51482
4.337150
842
51418
77436
25954
7
LyuwSEYBAPg
528175
4.425800
3752
528111
792479
264304
8
wzs4NzyWVB0
16073
3.928805
745
15839
24941
8868
9
Z-ZP7Jt-RUM
16607
4.258787
544
16482
25331
8724
In [83]:
expSum = df['Expectation'].sum()
print(expSum)
52419635
In [84]:
df['Probability'] = df['Expectation']/float(expSum)
df.head(10)
Out[84]:
id
nviews
rating
nrating
iniviews
eviews
Expectation
Probability
0
bG-a5ZSdO2I
21182
4.720000
418
21182
31773
10591
0.000202
1
46wXWDiigE8
13035
4.286420
486
12908
19990
6955
0.000133
2
X5h6xg7BcbQ
14543
4.553460
526
14479
22040
7497
0.000143
3
VKavlhLlZHc
1055
3.437303
89
990
1790
735
0.000014
4
DgGZL_rAR8U
22290
4.320078
643
22158
33889
11599
0.000221
5
CIm4ci3Y6iM
19436
4.566596
805
19372
29376
9940
0.000190
6
GOrNw5IeEB8
51482
4.337150
842
51418
77436
25954
0.000495
7
LyuwSEYBAPg
528175
4.425800
3752
528111
792479
264304
0.005042
8
wzs4NzyWVB0
16073
3.928805
745
15839
24941
8868
0.000169
9
Z-ZP7Jt-RUM
16607
4.258787
544
16482
25331
8724
0.000166
In [85]:
#for index, row in df.iterrows():
# print(index, "", row['Probability'])
In [86]:
#vids = dict()
#for index, row in df.iterrows():
# vids[index] = row['Probability']
#vids
In [87]:
#temp = tuple()
#vids2 = list()
#for index, row in df.iterrows():
# temp = (index,row['Probability'])
# vids2.append(temp)
#vids2
In [88]:
pdf = df.copy()
rdf = df.copy()
In [89]:
df.head(10)
Out[89]:
id
nviews
rating
nrating
iniviews
eviews
Expectation
Probability
0
bG-a5ZSdO2I
21182
4.720000
418
21182
31773
10591
0.000202
1
46wXWDiigE8
13035
4.286420
486
12908
19990
6955
0.000133
2
X5h6xg7BcbQ
14543
4.553460
526
14479
22040
7497
0.000143
3
VKavlhLlZHc
1055
3.437303
89
990
1790
735
0.000014
4
DgGZL_rAR8U
22290
4.320078
643
22158
33889
11599
0.000221
5
CIm4ci3Y6iM
19436
4.566596
805
19372
29376
9940
0.000190
6
GOrNw5IeEB8
51482
4.337150
842
51418
77436
25954
0.000495
7
LyuwSEYBAPg
528175
4.425800
3752
528111
792479
264304
0.005042
8
wzs4NzyWVB0
16073
3.928805
745
15839
24941
8868
0.000169
9
Z-ZP7Jt-RUM
16607
4.258787
544
16482
25331
8724
0.000166
In [90]:
pdf.head(10)
Out[90]:
id
nviews
rating
nrating
iniviews
eviews
Expectation
Probability
0
bG-a5ZSdO2I
21182
4.720000
418
21182
31773
10591
0.000202
1
46wXWDiigE8
13035
4.286420
486
12908
19990
6955
0.000133
2
X5h6xg7BcbQ
14543
4.553460
526
14479
22040
7497
0.000143
3
VKavlhLlZHc
1055
3.437303
89
990
1790
735
0.000014
4
DgGZL_rAR8U
22290
4.320078
643
22158
33889
11599
0.000221
5
CIm4ci3Y6iM
19436
4.566596
805
19372
29376
9940
0.000190
6
GOrNw5IeEB8
51482
4.337150
842
51418
77436
25954
0.000495
7
LyuwSEYBAPg
528175
4.425800
3752
528111
792479
264304
0.005042
8
wzs4NzyWVB0
16073
3.928805
745
15839
24941
8868
0.000169
9
Z-ZP7Jt-RUM
16607
4.258787
544
16482
25331
8724
0.000166
In [91]:
rdf.head(10)
Out[91]:
id
nviews
rating
nrating
iniviews
eviews
Expectation
Probability
0
bG-a5ZSdO2I
21182
4.720000
418
21182
31773
10591
0.000202
1
46wXWDiigE8
13035
4.286420
486
12908
19990
6955
0.000133
2
X5h6xg7BcbQ
14543
4.553460
526
14479
22040
7497
0.000143
3
VKavlhLlZHc
1055
3.437303
89
990
1790
735
0.000014
4
DgGZL_rAR8U
22290
4.320078
643
22158
33889
11599
0.000221
5
CIm4ci3Y6iM
19436
4.566596
805
19372
29376
9940
0.000190
6
GOrNw5IeEB8
51482
4.337150
842
51418
77436
25954
0.000495
7
LyuwSEYBAPg
528175
4.425800
3752
528111
792479
264304
0.005042
8
wzs4NzyWVB0
16073
3.928805
745
15839
24941
8868
0.000169
9
Z-ZP7Jt-RUM
16607
4.258787
544
16482
25331
8724
0.000166
In [92]:
df.ix[187]
Out[92]:
id fOIM1_xOSro
nviews 1543141
rating 4.53
nrating 2956
iniviews 1543141
eviews 2314711
Expectation 771570
Probability 0.0147191
Name: 187, dtype: object
In [93]:
pdf.ix[187]
Out[93]:
id fOIM1_xOSro
nviews 1543141
rating 4.53
nrating 2956
iniviews 1543141
eviews 2314711
Expectation 771570
Probability 0.0147191
Name: 187, dtype: object
In [94]:
rdf.ix[187]
Out[94]:
id fOIM1_xOSro
nviews 1543141
rating 4.53
nrating 2956
iniviews 1543141
eviews 2314711
Expectation 771570
Probability 0.0147191
Name: 187, dtype: object
In [95]:
vids3 = sorted([(index,row['Probability']) for index, row in pdf.iterrows()], key=lambda x: x[1], reverse=True)
vids3
Out[95]:
[(652, 0.07832030879268809),
(947, 0.03575456029024239),
(958, 0.03485930415196519),
(572, 0.029317277771964648),
(605, 0.022865992866985815),
(614, 0.022645846351276578),
(493, 0.021344711766878955),
(969, 0.02127761858700466),
(813, 0.021094633718834556),
(761, 0.016433231555313194),
(950, 0.015592840354573244),
(953, 0.015398066010951813),
(234, 0.015016281589904241),
(187, 0.014719102870517888),
(948, 0.013902634003460725),
(974, 0.0128893114192802),
(959, 0.012045162084779872),
(968, 0.011945027850728072),
(966, 0.01105837535877539),
(961, 0.010638780678270652),
(952, 0.010514018268154672),
(16, 0.010178895751563322),
(957, 0.01011723946570784),
(304, 0.009989424764212875),
(306, 0.009965616891456799),
(300, 0.009678014736272009),
(539, 0.008549887842599439),
(963, 0.008319477997128366),
(618, 0.008158278858675762),
(962, 0.008019609445964283),
(949, 0.00780903949445661),
(44, 0.007677523889664627),
(888, 0.0076141125362662295),
(967, 0.007377407339826002),
(558, 0.006747586090593725),
(232, 0.006675304015375155),
(825, 0.006579156836937152),
(951, 0.006537683827825203),
(960, 0.006511300584218108),
(15, 0.0064946083657392885),
(965, 0.0064818078187686735),
(783, 0.006161412608080922),
(954, 0.00552798583965722),
(560, 0.005467703084922282),
(688, 0.005175980336375864),
(23, 0.005146373109999717),
(620, 0.005111328989604754),
(7, 0.005042080128944049),
(819, 0.004982636754338332),
(994, 0.004823173606607524),
(229, 0.004786336265027408),
(956, 0.004734580849332507),
(821, 0.004675328242937976),
(506, 0.004390625764563221),
(846, 0.003984213167451471),
(496, 0.003973377533056077),
(146, 0.003799187079421671),
(993, 0.003715611526100859),
(76, 0.0035819783941647056),
(964, 0.0034573304449754374),
(685, 0.0034098100835688763),
(293, 0.0034002525961884323),
(127, 0.0033705499857066916),
(287, 0.003357081749996924),
(284, 0.0033393593831776967),
(77, 0.003325929301110166),
(824, 0.0032222658551514143),
(585, 0.0032075767028900528),
(283, 0.0031804685400804488),
(190, 0.003117743952242323),
(317, 0.0031009181960156723),
(992, 0.003070128206730169),
(89, 0.003012649744699672),
(98, 0.0029593300296730414),
(320, 0.0028719772657707365),
(86, 0.0028280433467344824),
(290, 0.0028132588103675273),
(476, 0.002784815270079618),
(786, 0.002766883058228086),
(750, 0.002736436451722718),
(78, 0.002660682395060553),
(880, 0.0025719561000377054),
(973, 0.0025493500670121035),
(158, 0.002543226407433016),
(975, 0.002539411043209286),
(986, 0.0025318375452251813),
(997, 0.002530006170397791),
(984, 0.0024870260924174693),
(227, 0.0024334202250740587),
(236, 0.0024054726821352342),
(604, 0.0022420415556117473),
(32, 0.002229603468242387),
(291, 0.002212930326584685),
(886, 0.002203868836553326),
(684, 0.0021353639719162484),
(755, 0.0021112317932011544),
(79, 0.002102132149527558),
(226, 0.0020994041641075904),
(706, 0.002085478084690975),
(297, 0.0020692055562767653),
(24, 0.0020545736344787595),
(285, 0.002036565115342753),
(756, 0.002023840875656612),
(289, 0.002007663731347996),
(312, 0.0020070341962510805),
(921, 0.002001311149915485),
(35, 0.0019746989844549663),
(817, 0.001931470907800102),
(955, 0.0019081971860353472),
(319, 0.0018982581622325298),
(322, 0.0018971135529654108),
(288, 0.0018776361186032676),
(160, 0.001811668471174971),
(47, 0.0017061164199254726),
(36, 0.0016981613855189949),
(122, 0.001683434079615396),
(237, 0.0016786648743357332),
(985, 0.0016050283448177387),
(221, 0.0015849786058220359),
(615, 0.0015223303252683846),
(331, 0.0015203654126931636),
(296, 0.001513326065700381),
(49, 0.0015075076352591924),
(51, 0.0015039975001733606),
(996, 0.0015005445955508848),
(995, 0.0014963286180836627),
(670, 0.0014913686445928134),
(292, 0.0014597774288203267),
(323, 0.001422215168037702),
(115, 0.0014140884422411564),
(295, 0.0014098533879528157),
(891, 0.0014075260157763404),
(74, 0.0014008872820270497),
(983, 0.001377937866221312),
(664, 0.001373988964249751),
(583, 0.001373283121868361),
(298, 0.0013645459377960186),
(977, 0.0013438094332400446),
(34, 0.0013358162451913296),
(309, 0.0013303030438880394),
(84, 0.001315766506195627),
(294, 0.0013101006903233875),
(686, 0.0012402222945657672),
(81, 0.001231809416452442),
(321, 0.0012301306561940007),
(149, 0.0012257620641578295),
(662, 0.0012193522522619626),
(124, 0.001208440310582094),
(999, 0.001192892701370393),
(667, 0.001174178339852996),
(815, 0.0011708208193361132),
(748, 0.0011408129797164746),
(315, 0.001128966273801792),
(979, 0.0011222703095891454),
(544, 0.0011040328685997145),
(759, 0.001103899330851884),
(254, 0.0010798816130635019),
(479, 0.001034345241053281),
(881, 0.0010295188053102622),
(970, 0.0010219262305050387),
(85, 0.0010087059934698133),
(231, 0.0010058444703020157),
(332, 0.0009909836266505862),
(21, 0.000988312871693975),
(669, 0.0009775535445830557),
(324, 0.0009773246227296317),
(413, 0.0009688545141529505),
(19, 0.0009617388598756935),
(746, 0.0009617197830545748),
(675, 0.0009506361499846384),
(256, 0.0008792125317164074),
(611, 0.0008574840324622634),
(301, 0.0008388269014082224),
(537, 0.0008228786789530297),
(238, 0.0008170793253329596),
(660, 0.0008131876538247548),
(749, 0.0008042215478989886),
(109, 0.0007968769717683078),
(11, 0.0007780099956819615),
(875, 0.000756262419606699),
(610, 0.0007559571904688005),
(303, 0.0007470673918275089),
(592, 0.0007421455719788968),
(666, 0.0007348963799538093),
(325, 0.0007236982859571609),
(613, 0.000718166007832752),
(980, 0.0007121758860014955),
(978, 0.0007116417350101732),
(600, 0.0007054036145043742),
(286, 0.000700596255582474),
(194, 0.0006783717589792451),
(437, 0.000661736770963781),
(329, 0.0006524654359001164),
(701, 0.0006507485219994379),
(616, 0.0006482113047906571),
(52, 0.000641763339252553),
(327, 0.0006402944240264169),
(45, 0.0006394931975394335),
(209, 0.0006369559803306528),
(700, 0.0006343806094796349),
(40, 0.000630927704857159),
(75, 0.0006302600161180061),
(41, 0.0006271886479179032),
(674, 0.0006133770294279997),
(243, 0.0006015494003344358),
(201, 0.0006006718665629778),
(80, 0.0005995844877592146),
(752, 0.000594967897048501),
(849, 0.0005936134427490768),
(596, 0.000582873192459276),
(326, 0.0005739261633546284),
(920, 0.000565742207094727),
(239, 0.0005624228402200817),
(97, 0.0005478290720643133),
(776, 0.0005475429197475335),
(88, 0.0005404654191125139),
(328, 0.0005401601899746154),
(703, 0.0005270162602238645),
(658, 0.0005246507344051518),
(671, 0.0005197289145565398),
(893, 0.0005158753966905722),
(18, 0.0005130138735227744),
(656, 0.0005124987993525708),
(219, 0.0005036662311746353),
(902, 0.0004960545795482933),
(6, 0.0004951198153134794),
(188, 0.0004943376656476147),
(91, 0.0004915142961220543),
(672, 0.00048762262461384936),
(763, 0.00048256726701740676),
(53, 0.0004799537425241515),
(155, 0.0004740590047984882),
(814, 0.00046776365382933323),
(971, 0.0004623649134527549),
(90, 0.0004571378644662444),
(308, 0.0004570424803606511),
(27, 0.0004522541982598696),
(54, 0.00044992682608339414),
(148, 0.0004495643664821398),
(82, 0.00044563454133169755),
(204, 0.0004338832195226083),
(606, 0.0004285607864305045),
(307, 0.00042608079968507983),
(823, 0.00041778238249846645),
(976, 0.00041673315733694065),
(136, 0.00041406240238032945),
(415, 0.00041060949775785353),
(680, 0.0004073664381676828),
(159, 0.0004058593692993093),
(820, 0.0004026353865302572),
(354, 0.000402540002424664),
(663, 0.00040002186203700197),
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In [96]:
b = vids3[0][1]
a = vids3[0][0]
print(b,a)
0.07832030879268809 652
In [97]:
lst2 = list()
for i in range(1000):
nodeSt = randint(0,99)
rate = 0
pardaught = dict()
exclu = list()
connected = list()
queue = [nodeSt]
visited_nodes = set()
lsttemp = list()
t = randint(0,1000000)
random.seed(t)
temp = randint(0,999)
while temp in lsttemp:
temp = randint(0,999)
lsttemp.append(temp)
if len(lsttemp) == 200:
lst2.extend(lsttemp)
del lsttemp[:]
vid = temp
#vid = randint(0,999)
#print(vid)
path = set()
connected.append(nodeSt)
lst2.append(vid)
for node in queue:
if node == nodeSt:
rdf.ix[vid,'nviews'] += 1
rdf.ix[vid,'eviews'] += 1
rate = randint(1,5)
r = rdf.ix[vid,'rating']
rdf.ix[vid,'rating'] = ((rdf.ix[vid,'nrating'] * r) + rate)/float(rdf.ix[vid,'nrating'] + 1)
rdf.ix[vid,'nrating'] += 1
#print(G.node[node])
neighbors = G.neighbors(node)
#exclu = [n for n in neighbors if n not in visited_nodes]
exclu = [n for n in neighbors if n not in connected]
pardaught[node] = exclu
connected.extend(exclu)
#queue.remove(node)
visited_nodes.add(node)
path.add(node)
queue.extend(exclu)
rdf.ix[vid,'eviews'] += len(neighbors)
#print(str(node) + " viewed & shared")
else:
for key, values in pardaught.items():
if node in values:
parent = key
if VwR_thr <= (rdf.ix[vid,'rating']*G.node[node]['ViRt']*G.node[parent]['Attractiveness_Coeff']):
rdf.ix[vid,'nviews'] += 1
rdf.ix[vid,'eviews'] += 1
#print(str(node) + " viewed")
rate = randint(1,5)
r = rdf.ix[vid,'rating']
rdf.ix[vid,'rating'] = ((rdf.ix[vid,'nrating'] * r) + rate)/float(rdf.ix[vid,'nrating'] + 1)
rdf.ix[vid,'nrating'] += 1
if ShR_thr <= (rdf.ix[vid,'rating']*G.node[node]['Sharing_Rate']*G.node[parent]['Attractiveness_Coeff']):
#print(G.node[node])
neighbors = G.neighbors(node)
exclu = [n for n in neighbors if n not in connected]
pardaught[node] = exclu
connected.extend(exclu)
#queue.remove(node)
visited_nodes.add(node)
path.add(node)
queue.extend(exclu)
rdf.ix[vid,'eviews'] += len(neighbors)
#print(str(node) + " shared")# rdf['Expectation'] = rdf['eviews'] - rdf['nviews'] expSum = rdf['Expectation'].sum() rdf['Probability'] = rdf['Expectation']/float(expSum)
#lst2.sort()
#print(lst2)
print(path)
{76}
In [98]:
#newG = G.subgraph(path)
#nx.draw(newG, with_labels=True)
In [99]:
#a = np.arange(1,1001)
#p1 = np.random.choice(a,size=100,replace=0)
#p2 = np.setdiff1d(a,p1)
#p1_idx = np.random.randint(0,p1.size,(8000))
#p2_idx = np.random.randint(0,p2.size,(2000))
#out = np.random.permutation(np.hstack((p1[p1_idx], p2[p2_idx])))
#lst2 = list(out)
In [100]:
#lstdf3 = [a for a,b in vids3]
#frequent = lstdf3[:50]
#rare = lstdf3[50:]
In [101]:
#lst = list()
#idx = 0
random.seed(10)
for i in range(1000):
#t = random.randint(0,10000)
#random.seed(t)
nodeSt = randint(0,99)
rate = 0
pardaught = dict()
exclu = list()
connected = list()
queue = [nodeSt]
visited_nodes = set()
vids = sorted([(index,row['Probability']) for index, row in pdf.iterrows()], key=lambda x: x[1], reverse=True)
lstdf3 = [a for a,b in vids]
frequent = lstdf3[:10]
rare = lstdf3[10:]
#t = random.randint(0,10000)
#random.seed(t)
#temp = randint(0,100)
a = random.randint(1,10)
if a == 1:
# Case for rare numbers
choice = random.choice(rare)
else:
# case for frequent numbers
choice = random.choice(frequent)
#temp = lst[idx]
#idx += 1
#vid = vids[temp][0]
#print(vid)
vid = vids[choice][0]
path = set()
connected.append(nodeSt)
lst.append(vid)
#lst.append(pdf.ix[vid,'Probability'])
for node in queue:
if node == nodeSt:
pdf.ix[vid,'nviews'] += 1
pdf.ix[vid,'eviews'] += 1
t = random.randint(0,10000)
random.seed(t)
rate = randint(1,5)
r = pdf.ix[vid,'rating']
pdf.ix[vid,'rating'] = ((pdf.ix[vid,'nrating'] * r) + rate)/float(pdf.ix[vid,'nrating'] + 1)
pdf.ix[vid,'nrating'] += 1
#print(G.node[node])
neighbors = G.neighbors(node)
#exclu = [n for n in neighbors if n not in visited_nodes]
exclu = [n for n in neighbors if n not in connected]
pardaught[node] = exclu
connected.extend(exclu)
#queue.remove(node)
visited_nodes.add(node)
path.add(node)
queue.extend(exclu)
pdf.ix[vid,'eviews'] += len(neighbors)
#print(str(node) + " viewed & shared")
else:
for key, values in pardaught.items():
if node in values:
parent = key
if VwR_thr <= (pdf.ix[vid,'rating']*G.node[node]['ViRt']*G.node[parent]['Attractiveness_Coeff']):
pdf.ix[vid,'nviews'] += 1
pdf.ix[vid,'eviews'] += 1
#print(str(node) + " viewed")
rate = randint(1,5)
r = pdf.ix[vid,'rating']
pdf.ix[vid,'rating'] = ((pdf.ix[vid,'nrating'] * r) + rate)/float(pdf.ix[vid,'nrating'] + 1)
pdf.ix[vid,'nrating'] += 1
if ShR_thr <= (pdf.ix[vid,'rating']*G.node[node]['Sharing_Rate']*G.node[parent]['Attractiveness_Coeff']):
#print(G.node[node])
neighbors = G.neighbors(node)
exclu = [n for n in neighbors if n not in connected]
pardaught[node] = exclu
connected.extend(exclu)
#queue.remove(node)
visited_nodes.add(node)
path.add(node)
queue.extend(exclu)
pdf.ix[vid,'eviews'] += len(neighbors)
#print(str(node) + " shared")
pdf['Expectation'] = pdf['eviews'] - pdf['nviews']
expSum = pdf['Expectation'].sum()
pdf['Probability'] = pdf['Expectation']/float(expSum)
#lst.sort()
#print(lst)
In [102]:
#newG = G.subgraph(path)
#nx.draw(newG, with_labels=True)
In [103]:
#common = [element for element in lst if element in lst2]
#common
In [104]:
pdf.head()
Out[104]:
id
nviews
rating
nrating
iniviews
eviews
Expectation
Probability
0
bG-a5ZSdO2I
21182
4.720000
418
21182
31773
10591
0.000202
1
46wXWDiigE8
13035
4.286420
486
12908
19990
6955
0.000132
2
X5h6xg7BcbQ
14543
4.553460
526
14479
22040
7497
0.000143
3
VKavlhLlZHc
1055
3.437303
89
990
1790
735
0.000014
4
DgGZL_rAR8U
22290
4.320078
643
22158
33889
11599
0.000221
In [105]:
df.head()
Out[105]:
id
nviews
rating
nrating
iniviews
eviews
Expectation
Probability
0
bG-a5ZSdO2I
21182
4.720000
418
21182
31773
10591
0.000202
1
46wXWDiigE8
13035
4.286420
486
12908
19990
6955
0.000133
2
X5h6xg7BcbQ
14543
4.553460
526
14479
22040
7497
0.000143
3
VKavlhLlZHc
1055
3.437303
89
990
1790
735
0.000014
4
DgGZL_rAR8U
22290
4.320078
643
22158
33889
11599
0.000221
In [106]:
#rdf.head()
In [107]:
df.ix[493]
Out[107]:
id kdWrCTMuQ1M
nviews 2237765
rating 4.15
nrating 1793
iniviews 2237765
eviews 3356647
Expectation 1118882
Probability 0.0213447
Name: 493, dtype: object
In [108]:
pdf.ix[493]
Out[108]:
id kdWrCTMuQ1M
nviews 2237765
rating 4.15
nrating 1793
iniviews 2237765
eviews 3356647
Expectation 1118882
Probability 0.0213023
Name: 493, dtype: object
In [109]:
#rdf.ix[493]
In [110]:
vidsdf = sorted([(index,row['nviews']) for index, row in df.iterrows()], key=lambda x: x[1], reverse=True)
vidspdf = sorted([(index,row['nviews']) for index, row in pdf.iterrows()], key=lambda x: x[1], reverse=True)
vidsrdf = sorted([(index,row['nviews']) for index, row in rdf.iterrows()], key=lambda x: x[1], reverse=True)
In [111]:
lstdf = [b for a,b in vidsdf]
lstpdf = [b for a,b in vidspdf]
lstrdf = [b for a,b in vidsrdf]
In [112]:
krange = list(range(len(lstdf)))
In [113]:
print(lstpdf)
[8211045, 3748482, 3654625, 3073603, 2397255, 2374175, 2237765, 2230731, 2211614, 1722849, 1634743, 1614326, 1574296, 1543141, 1457542, 1351306, 1262807, 1252309, 1159355, 1115362, 1102283, 1065835, 1060684, 1047284, 1044789, 1014637, 896365, 872209, 855308, 840771, 818695, 803036, 798259, 773505, 707413, 699834, 689754, 685407, 682641, 679548, 678722, 645959, 579550, 573230, 542709, 539102, 535869, 528175, 522377, 505658, 501797, 496370, 490158, 460311, 417702, 416566, 398371, 389543, 375532, 362465, 357534, 356542, 353366, 351955, 350097, 348689, 337820, 336280, 333439, 326863, 325099, 321871, 315844, 310255, 301096, 296490, 294940, 291958, 290078, 286886, 278945, 269642, 267272, 266631, 266230, 265436, 265245, 260739, 255118, 252248, 235055, 232509, 232003, 231053, 223871, 221341, 220387, 220100, 218641, 216934, 214946, 213513, 212229, 210482, 210417, 209816, 206165, 202495, 200054, 199012, 198893, 196850, 189934, 178064, 176749, 176491, 175990, 168271, 166169, 159600, 159394, 158656, 158044, 157679, 157316, 156875, 156355, 153043, 149105, 148252, 147809, 147564, 146869, 144462, 144048, 143975, 143058, 140885, 140047, 139469, 137945, 137352, 130025, 129142, 128966, 128508, 127900, 126692, 125062, 123100, 122748, 119603, 118360, 117658, 115746, 115733, 113215, 108440, 107935, 107139, 105753, 105453, 103895, 103260, 102487, 102462, 101575, 100827, 99892, 99664, 92177, 89898, 87942, 86271, 85662, 85254, 84315, 83604, 81565, 79287, 79254, 78323, 77806, 77047, 75872, 75292, 74664, 74609, 73954, 73450, 71120, 69377, 68405, 68225, 67958, 67282, 67129, 66835, 66508, 66243, 66077, 65346, 65239, 64366, 63067, 62975, 62860, 62376, 62234, 61172, 60170, 59313, 58964, 57435, 57405, 56722, 56694, 55253, 55004, 54489, 54085, 53782, 53731, 52805, 52007, 51827, 51531, 51482, 51123, 50593, 50319, 49701, 49040, 48474, 47926, 47917, 47415, 47171, 47133, 46721, 45489, 44931, 44671, 43800, 43750, 43410, 43048, 42709, 42551, 42213, 42203, 41938, 41783, 41596, 39862, 39512, 39141, 38763, 38694, 38121, 37962, 37450, 37325, 36005, 35964, 35143, 35050, 34196, 33888, 33857, 33602, 32804, 32642, 32633, 32594, 32475, 32195, 32179, 31509, 31460, 31122, 30952, 30587, 30451, 30405, 30166, 30040, 29825, 29790, 29772, 29751, 29309, 29281, 29091, 28498, 28038, 27195, 26984, 26730, 26623, 26608, 26270, 26159, 26084, 26076, 26051, 26042, 25966, 25925, 25370, 25120, 24386, 24316, 23844, 23784, 23742, 23595, 23124, 22290, 21891, 21852, 21794, 21722, 21720, 21716, 21276, 21258, 21182, 20982, 20963, 20606, 20378, 20353, 19965, 19940, 19938, 19518, 19436, 19352, 18990, 18955, 18801, 18728, 18621, 18256, 18250, 18217, 18110, 17907, 17662, 17582, 17410, 17316, 17217, 17063, 16894, 16813, 16800, 16765, 16670, 16665, 16607, 16381, 16325, 16073, 16071, 15734, 15262, 15194, 15144, 15109, 15107, 15041, 14929, 14893, 14558, 14543, 14499, 13815, 13779, 13602, 13593, 13400, 13343, 13294, 13277, 13147, 13035, 13024, 12974, 12861, 12706, 12661, 12500, 12464, 12383, 12321, 12117, 12095, 12042, 12009, 11984, 11904, 11823, 11817, 11793, 11769, 11729, 11696, 11657, 11643, 11568, 11537, 11424, 11417, 11375, 11187, 10968, 10867, 10859, 10662, 10650, 10595, 10510, 10471, 10365, 10207, 10022, 10003, 9987, 9889, 9510, 9471, 9458, 9418, 9417, 9293, 9256, 9242, 9234, 9228, 9226, 9208, 9201, 9175, 9167, 9096, 9066, 8931, 8920, 8918, 8893, 8867, 8851, 8832, 8770, 8758, 8758, 8746, 8608, 8589, 8558, 8421, 8386, 8359, 8354, 8349, 8331, 8323, 8322, 8306, 8284, 8182, 8044, 7999, 7976, 7883, 7815, 7815, 7766, 7673, 7624, 7550, 7536, 7443, 7409, 7346, 7293, 7283, 7280, 7224, 7195, 7171, 7044, 6855, 6836, 6713, 6640, 6509, 6503, 6493, 6451, 6444, 6420, 6337, 6330, 6303, 6218, 6204, 6185, 6159, 6089, 6079, 6075, 5948, 5928, 5880, 5857, 5842, 5836, 5824, 5744, 5716, 5709, 5693, 5567, 5565, 5500, 5498, 5492, 5460, 5422, 5344, 5302, 5280, 5265, 5222, 5203, 5160, 5146, 5114, 5088, 5076, 5035, 4999, 4965, 4958, 4842, 4806, 4794, 4775, 4770, 4750, 4732, 4728, 4710, 4703, 4621, 4581, 4521, 4446, 4432, 4410, 4350, 4349, 4341, 4326, 4325, 4235, 4230, 4215, 4094, 4068, 4027, 3976, 3975, 3906, 3874, 3789, 3730, 3721, 3695, 3637, 3635, 3621, 3620, 3556, 3506, 3503, 3457, 3455, 3443, 3437, 3404, 3375, 3358, 3357, 3327, 3319, 3312, 3277, 3268, 3241, 3237, 3224, 3223, 3214, 3201, 3163, 3154, 3135, 3131, 3043, 3037, 3003, 2825, 2789, 2765, 2758, 2756, 2723, 2688, 2636, 2578, 2539, 2528, 2504, 2485, 2479, 2478, 2448, 2447, 2419, 2415, 2413, 2398, 2393, 2390, 2376, 2363, 2362, 2337, 2328, 2313, 2301, 2291, 2275, 2223, 2220, 2196, 2187, 2117, 2078, 2072, 2068, 2067, 2063, 2001, 2000, 1998, 1983, 1971, 1925, 1913, 1905, 1900, 1887, 1845, 1737, 1695, 1678, 1658, 1658, 1658, 1652, 1642, 1616, 1615, 1561, 1561, 1554, 1554, 1546, 1493, 1492, 1490, 1480, 1478, 1477, 1473, 1467, 1466, 1466, 1460, 1460, 1453, 1443, 1436, 1429, 1418, 1415, 1386, 1383, 1379, 1374, 1359, 1353, 1351, 1349, 1338, 1302, 1289, 1287, 1258, 1243, 1239, 1213, 1210, 1209, 1197, 1179, 1177, 1168, 1160, 1144, 1130, 1122, 1118, 1110, 1090, 1074, 1055, 1045, 1045, 1041, 1021, 1017, 974, 972, 956, 950, 950, 924, 920, 917, 909, 908, 903, 894, 894, 890, 884, 879, 876, 874, 858, 855, 838, 825, 821, 810, 808, 808, 801, 793, 790, 787, 784, 780, 780, 775, 766, 763, 754, 751, 750, 748, 740, 734, 730, 724, 717, 716, 704, 702, 699, 695, 690, 670, 666, 663, 660, 655, 645, 645, 642, 632, 630, 629, 624, 617, 606, 602, 592, 592, 573, 569, 541, 537, 519, 519, 500, 493, 492, 490, 475, 471, 471, 470, 466, 461, 459, 442, 441, 439, 438, 438, 433, 432, 430, 428, 428, 427, 425, 411, 405, 404, 403, 400, 396, 393, 393, 391, 390, 387, 386, 383, 379, 371, 369, 366, 365, 365, 364, 360, 359, 358, 355, 355, 355, 351, 349, 347, 346, 344, 342, 342, 341, 334, 332, 331, 330, 329, 326, 325, 324, 324, 321, 317, 315, 314, 313, 312, 309, 304, 298, 295, 295, 294, 292, 290, 290, 288, 288, 288, 282, 282, 276, 270, 261, 259, 254, 253, 253, 253, 252, 251, 247, 247, 245, 243, 243, 242, 242, 239, 237, 237, 235, 235, 232, 230, 229, 225, 220, 220, 218, 212, 209, 203, 202, 198, 196, 192, 190, 184, 184, 184, 181, 179, 176, 174, 173, 167, 166, 163, 163, 160, 156, 154, 151, 144, 142, 139, 139, 134, 132, 131, 129, 128, 125, 124, 118, 115, 114, 111, 105, 102, 100, 92, 65, 56, 55, 53, 52, 51, 50, 50, 47, 46, 44, 41, 41, 38, 38, 35, 34, 33, 33, 33, 32, 29, 29, 29, 26, 24, 24, 23, 22, 15, 9]
In [114]:
#plt.plot(krange,lstdf)
#plt.xlabel('Rank')
#plt.ylabel('Number of views')
In [115]:
#plt.plot(krange,lstpdf)
#plt.xlabel('Rank')
#plt.ylabel('Number of views')
In [116]:
import numpy as np
#plt.plot(np.linspace(0,1, len(krange)), lstpdf)
In [117]:
pdf['diff'] = pdf['nviews'] - pdf['iniviews']
In [118]:
vidspdfdiff = sorted([(index,row['diff']) for index, row in pdf.iterrows()], key=lambda x: x[1], reverse=True)
In [119]:
lstpdfdiff = [b for a,b in vidspdfdiff]
In [120]:
#plt.plot(np.linspace(0,1, len(krange)), lstpdfdiff)
In [121]:
sum = 0
#lstpdfdiff.reverse()
In [122]:
for i in range(len(lstpdfdiff)):
temp = lstpdfdiff[i]
lstpdfdiff[i] = lstpdfdiff[i] + sum
sum += temp
In [123]:
for i in range(len(lstpdf)):
temp = lstpdf[i]
lstpdf[i] = lstpdf[i] + sum
sum += temp
In [124]:
print(lstpdf)
[8245418, 11993900, 15648525, 18722128, 21119383, 23493558, 25731323, 27962054, 30173668, 31896517, 33531260, 35145586, 36719882, 38263023, 39720565, 41071871, 42334678, 43586987, 44746342, 45861704, 46963987, 48029822, 49090506, 50137790, 51182579, 52197216, 53093581, 53965790, 54821098, 55661869, 56480564, 57283600, 58081859, 58855364, 59562777, 60262611, 60952365, 61637772, 62320413, 62999961, 63678683, 64324642, 64904192, 65477422, 66020131, 66559233, 67095102, 67623277, 68145654, 68651312, 69153109, 69649479, 70139637, 70599948, 71017650, 71434216, 71832587, 72222130, 72597662, 72960127, 73317661, 73674203, 74027569, 74379524, 74729621, 75078310, 75416130, 75752410, 76085849, 76412712, 76737811, 77059682, 77375526, 77685781, 77986877, 78283367, 78578307, 78870265, 79160343, 79447229, 79726174, 79995816, 80263088, 80529719, 80795949, 81061385, 81326630, 81587369, 81842487, 82094735, 82329790, 82562299, 82794302, 83025355, 83249226, 83470567, 83690954, 83911054, 84129695, 84346629, 84561575, 84775088, 84987317, 85197799, 85408216, 85618032, 85824197, 86026692, 86226746, 86425758, 86624651, 86821501, 87011435, 87189499, 87366248, 87542739, 87718729, 87887000, 88053169, 88212769, 88372163, 88530819, 88688863, 88846542, 89003858, 89160733, 89317088, 89470131, 89619236, 89767488, 89915297, 90062861, 90209730, 90354192, 90498240, 90642215, 90785273, 90926158, 91066205, 91205674, 91343619, 91480971, 91610996, 91740138, 91869104, 91997612, 92125512, 92252204, 92377266, 92500366, 92623114, 92742717, 92861077, 92978735, 93094481, 93210214, 93323429, 93431869, 93539804, 93646943, 93752696, 93858149, 93962044, 94065304, 94167791, 94270253, 94371828, 94472655, 94572547, 94672211, 94764388, 94854286, 94942228, 95028499, 95114161, 95199415, 95283730, 95367334, 95448899, 95528186, 95607440, 95685763, 95763569, 95840616, 95916488, 95991780, 96066444, 96141053, 96215007, 96288457, 96359577, 96428954, 96497359, 96565584, 96633542, 96700824, 96767953, 96834788, 96901296, 96967539, 97033616, 97098962, 97164201, 97228567, 97291634, 97354609, 97417469, 97479845, 97542079, 97603251, 97663421, 97722734, 97781698, 97839133, 97896538, 97953260, 98009954, 98065207, 98120211, 98174700, 98228785, 98282567, 98336298, 98389103, 98441110, 98492937, 98544468, 98595950, 98647073, 98697666, 98747985, 98797686, 98846726, 98895200, 98943126, 98991043, 99038458, 99085629, 99132762, 99179483, 99224972, 99269903, 99314574, 99358374, 99402124, 99445534, 99488582, 99531291, 99573842, 99616055, 99658258, 99700196, 99741979, 99783575, 99823437, 99862949, 99902090, 99940853, 99979547, 100017668, 100055630, 100093080, 100130405, 100166410, 100202374, 100237517, 100272567, 100306763, 100340651, 100374508, 100408110, 100440914, 100473556, 100506189, 100538783, 100571258, 100603453, 100635632, 100667141, 100698601, 100729723, 100760675, 100791262, 100821713, 100852118, 100882284, 100912324, 100942149, 100971939, 101001711, 101031462, 101060771, 101090052, 101119143, 101147641, 101175679, 101202874, 101229858, 101256588, 101283211, 101309819, 101336089, 101362248, 101388332, 101414408, 101440459, 101466501, 101492467, 101518392, 101543762, 101568882, 101593268, 101617584, 101641428, 101665212, 101688954, 101712549, 101735673, 101757963, 101779854, 101801706, 101823500, 101845222, 101866942, 101888658, 101909934, 101931192, 101952374, 101973356, 101994319, 102014925, 102035303, 102055656, 102075621, 102095561, 102115499, 102135017, 102154453, 102173805, 102192795, 102211750, 102230551, 102249279, 102267900, 102286156, 102304406, 102322623, 102340733, 102358640, 102376302, 102393884, 102411294, 102428610, 102445827, 102462890, 102479784, 102496597, 102513397, 102530162, 102546832, 102563497, 102580104, 102596485, 102612810, 102628883, 102644954, 102660688, 102675950, 102691144, 102706288, 102721397, 102736504, 102751545, 102766474, 102781367, 102795925, 102810468, 102824967, 102838782, 102852561, 102866163, 102879756, 102893156, 102906499, 102919793, 102933070, 102946217, 102959252, 102972276, 102985250, 102998111, 103010817, 103023478, 103035978, 103048442, 103060825, 103073146, 103085263, 103097358, 103109400, 103121409, 103133393, 103145297, 103157120, 103168937, 103180730, 103192499, 103204228, 103215924, 103227581, 103239224, 103250792, 103262329, 103273753, 103285170, 103296545, 103307732, 103318700, 103329567, 103340426, 103351088, 103361738, 103372333, 103382843, 103393314, 103403679, 103413886, 103423908, 103433911, 103443898, 103453787, 103463297, 103472768, 103482226, 103491644, 103501061, 103510354, 103519610, 103528852, 103538086, 103547314, 103556540, 103565748, 103574949, 103584124, 103593291, 103602387, 103611453, 103620384, 103629304, 103638222, 103647115, 103655982, 103664833, 103673665, 103682435, 103691193, 103699951, 103708697, 103717305, 103725894, 103734452, 103742873, 103751259, 103759618, 103767972, 103776321, 103784652, 103792975, 103801297, 103809603, 103817887, 103826069, 103834113, 103842112, 103850088, 103857971, 103865786, 103873601, 103881367, 103889040, 103896664, 103904214, 103911750, 103919193, 103926602, 103933948, 103941241, 103948524, 103955804, 103963028, 103970223, 103977394, 103984438, 103991293, 103998129, 104004842, 104011482, 104017991, 104024494, 104030987, 104037438, 104043882, 104050302, 104056639, 104062969, 104069272, 104075490, 104081694, 104087879, 104094038, 104100127, 104106206, 104112281, 104118229, 104124157, 104130037, 104135894, 104141736, 104147572, 104153396, 104159140, 104164856, 104170565, 104176258, 104181825, 104187390, 104192890, 104198388, 104203880, 104209340, 104214762, 104220106, 104225408, 104230688, 104235953, 104241175, 104246378, 104251538, 104256684, 104261798, 104266886, 104271962, 104276997, 104281996, 104286961, 104291919, 104296761, 104301567, 104306361, 104311136, 104315906, 104320656, 104325388, 104330116, 104334826, 104339529, 104344150, 104348731, 104353252, 104357698, 104362130, 104366540, 104370890, 104375239, 104379580, 104383906, 104388231, 104392466, 104396696, 104400911, 104405005, 104409073, 104413100, 104417076, 104421051, 104424957, 104428831, 104432620, 104436350, 104440071, 104443766, 104447403, 104451038, 104454659, 104458279, 104461835, 104465341, 104468844, 104472301, 104475756, 104479199, 104482636, 104486040, 104489415, 104492773, 104496130, 104499457, 104502776, 104506088, 104509365, 104512633, 104515874, 104519111, 104522335, 104525558, 104528772, 104531973, 104535136, 104538290, 104541425, 104544556, 104547599, 104550636, 104553639, 104556464, 104559253, 104562018, 104564776, 104567532, 104570255, 104572943, 104575579, 104578157, 104580696, 104583224, 104585728, 104588213, 104590692, 104593170, 104595618, 104598065, 104600484, 104602899, 104605312, 104607710, 104610103, 104612493, 104614869, 104617232, 104619594, 104621931, 104624259, 104626572, 104628873, 104631164, 104633439, 104635662, 104637882, 104640078, 104642265, 104644382, 104646460, 104648532, 104650600, 104652667, 104654730, 104656731, 104658731, 104660729, 104662712, 104664683, 104666608, 104668521, 104670426, 104672326, 104674213, 104676058, 104677795, 104679490, 104681168, 104682826, 104684484, 104686142, 104687794, 104689436, 104691052, 104692667, 104694228, 104695789, 104697343, 104698897, 104700443, 104701936, 104703428, 104704918, 104706398, 104707876, 104709353, 104710826, 104712293, 104713759, 104715225, 104716685, 104718145, 104719598, 104721041, 104722477, 104723906, 104725324, 104726739, 104728125, 104729508, 104730887, 104732261, 104733620, 104734973, 104736324, 104737673, 104739011, 104740313, 104741602, 104742889, 104744147, 104745390, 104746629, 104747842, 104749052, 104750261, 104751458, 104752637, 104753814, 104754982, 104756142, 104757286, 104758416, 104759538, 104760656, 104761766, 104762856, 104763930, 104764985, 104766030, 104767075, 104768116, 104769137, 104770154, 104771128, 104772100, 104773056, 104774006, 104774956, 104775880, 104776800, 104777717, 104778626, 104779534, 104780437, 104781331, 104782225, 104783115, 104783999, 104784878, 104785754, 104786628, 104787486, 104788341, 104789179, 104790004, 104790825, 104791635, 104792443, 104793251, 104794052, 104794845, 104795635, 104796422, 104797206, 104797986, 104798766, 104799541, 104800307, 104801070, 104801824, 104802575, 104803325, 104804073, 104804813, 104805547, 104806277, 104807001, 104807718, 104808434, 104809138, 104809840, 104810539, 104811234, 104811924, 104812594, 104813260, 104813923, 104814583, 104815238, 104815883, 104816528, 104817170, 104817802, 104818432, 104819061, 104819685, 104820302, 104820908, 104821510, 104822102, 104822694, 104823267, 104823836, 104824377, 104824914, 104825433, 104825952, 104826452, 104826945, 104827437, 104827927, 104828402, 104828873, 104829344, 104829814, 104830280, 104830741, 104831200, 104831642, 104832083, 104832522, 104832960, 104833398, 104833831, 104834263, 104834693, 104835121, 104835549, 104835976, 104836401, 104836812, 104837217, 104837621, 104838024, 104838424, 104838820, 104839213, 104839606, 104839997, 104840387, 104840774, 104841160, 104841543, 104841922, 104842293, 104842662, 104843028, 104843393, 104843758, 104844122, 104844482, 104844841, 104845199, 104845554, 104845909, 104846264, 104846615, 104846964, 104847311, 104847657, 104848001, 104848343, 104848685, 104849026, 104849360, 104849692, 104850023, 104850353, 104850682, 104851008, 104851333, 104851657, 104851981, 104852302, 104852619, 104852934, 104853248, 104853561, 104853873, 104854182, 104854486, 104854784, 104855079, 104855374, 104855668, 104855960, 104856250, 104856540, 104856828, 104857116, 104857404, 104857686, 104857968, 104858244, 104858514, 104858775, 104859034, 104859288, 104859541, 104859794, 104860047, 104860299, 104860550, 104860797, 104861044, 104861289, 104861532, 104861775, 104862017, 104862259, 104862498, 104862735, 104862972, 104863207, 104863442, 104863674, 104863904, 104864133, 104864358, 104864578, 104864798, 104865016, 104865228, 104865437, 104865640, 104865842, 104866040, 104866236, 104866428, 104866618, 104866802, 104866986, 104867170, 104867351, 104867530, 104867706, 104867880, 104868053, 104868220, 104868386, 104868549, 104868712, 104868872, 104869028, 104869182, 104869333, 104869477, 104869619, 104869758, 104869897, 104870031, 104870163, 104870294, 104870423, 104870551, 104870676, 104870800, 104870918, 104871033, 104871147, 104871258, 104871363, 104871465, 104871565, 104871657, 104871722, 104871778, 104871833, 104871886, 104871938, 104871989, 104872039, 104872089, 104872136, 104872182, 104872226, 104872267, 104872308, 104872346, 104872384, 104872419, 104872453, 104872486, 104872519, 104872552, 104872584, 104872613, 104872642, 104872671, 104872697, 104872721, 104872745, 104872768, 104872790, 104872805, 104872814]
In [125]:
#lstpdfdiff.reverse()
In [128]:
plt.plot(np.linspace(0,1, len(krange)), lstpdf, label='Cumulative views')
plt.xlabel('Normalized video index(ranked by popularity)', fontsize=10)
plt.ylabel('Total Number of views', fontsize=10)
plt.yscale('log')
plt.ylim(0, 200000000)
plt.legend(loc='upper center', bbox_to_anchor=(0.5, 0.5), ncol=1, fancybox=True, shadow=True)
plt.grid(True)
In [127]:
#lstpdfdiff2 = [b for a,b in vidspdfdiff]
#plt.plot(np.linspace(0,1, len(krange)), lstpdfdiff2, label='Views')
#plt.xlabel('Normalized video index(ranked by popularity)', fontsize=10)
#plt.ylabel('Number of views', fontsize=10)
#plt.yscale('log')
#plt.ylim(0, 50000)
#plt.legend(loc='upper center', bbox_to_anchor=(0.5, 0.5), ncol=1, fancybox=True, shadow=True)
#plt.grid(True)
In [125]:
#print(lstpdfdiff)
In [126]:
pdf2 = pdf.copy()
pdf3 = pdf.copy()
In [127]:
#plt.plot(krange,lstrdf)
#plt.xlabel('Rank')
#plt.ylabel('Number of views')
In [128]:
print(lstpdfdiff)
[1126, 1528, 1927, 2323, 2711, 3091, 3465, 3839, 4207, 4566, 4902, 5220, 5537, 5841, 6135, 6427, 6707, 6982, 7226, 7464, 7699, 7933, 8165, 8357, 8547, 8730, 8907, 9078, 9243, 9407, 9567, 9723, 9878, 10021, 10159, 10297, 10432, 10564, 10696, 10827, 10957, 11086, 11214, 11341, 11468, 11594, 11720, 11845, 11969, 12093, 12216, 12339, 12462, 12584, 12705, 12825, 12945, 13064, 13183, 13302, 13420, 13537, 13654, 13771, 13888, 14005, 14121, 14236, 14351, 14466, 14581, 14695, 14809, 14923, 15037, 15150, 15263, 15375, 15487, 15598, 15709, 15820, 15930, 16039, 16148, 16257, 16366, 16474, 16582, 16690, 16798, 16906, 17014, 17122, 17229, 17336, 17443, 17549, 17655, 17759, 17862, 17964, 18066, 18167, 18268, 18369, 18468, 18566, 18664, 18761, 18858, 18954, 19050, 19146, 19242, 19338, 19433, 19528, 19621, 19714, 19806, 19897, 19988, 20079, 20169, 20259, 20349, 20438, 20527, 20615, 20702, 20788, 20874, 20959, 21043, 21127, 21210, 21290, 21367, 21443, 21517, 21591, 21664, 21737, 21808, 21879, 21950, 22020, 22089, 22157, 22225, 22292, 22359, 22426, 22493, 22560, 22626, 22692, 22758, 22824, 22889, 22954, 23019, 23084, 23148, 23212, 23276, 23340, 23404, 23468, 23532, 23596, 23660, 23724, 23788, 23852, 23916, 23979, 24042, 24105, 24167, 24229, 24291, 24353, 24415, 24477, 24538, 24599, 24660, 24721, 24782, 24843, 24904, 24965, 25025, 25085, 25145, 25205, 25265, 25325, 25385, 25445, 25505, 25565, 25625, 25685, 25745, 25805, 25864, 25923, 25982, 26041, 26100, 26159, 26218, 26277, 26336, 26395, 26454, 26513, 26572, 26631, 26690, 26749, 26807, 26865, 26923, 26981, 27039, 27097, 27155, 27213, 27271, 27329, 27387, 27445, 27503, 27561, 27619, 27677, 27735, 27793, 27850, 27907, 27964, 28021, 28078, 28135, 28192, 28249, 28306, 28363, 28420, 28477, 28534, 28590, 28646, 28702, 28758, 28814, 28870, 28926, 28982, 29038, 29094, 29150, 29206, 29262, 29318, 29374, 29430, 29486, 29542, 29598, 29654, 29709, 29764, 29819, 29874, 29929, 29984, 30039, 30094, 30149, 30204, 30259, 30314, 30369, 30423, 30477, 30531, 30585, 30639, 30693, 30747, 30801, 30855, 30909, 30963, 31017, 31071, 31124, 31177, 31230, 31283, 31336, 31389, 31442, 31495, 31548, 31600, 31652, 31704, 31756, 31808, 31860, 31912, 31964, 32016, 32068, 32120, 32172, 32223, 32274, 32325, 32376, 32427, 32477, 32527, 32576, 32625, 32674, 32723, 32772, 32821, 32870, 32918, 32966, 33014, 33062, 33110, 33157, 33204, 33251, 33297, 33343, 33389, 33435, 33481, 33527, 33572, 33617, 33662, 33706, 33750, 33794, 33837, 33880, 33923, 33966, 34009, 34051, 34093, 34135, 34177, 34218, 34259, 34300, 34340, 34379, 34418, 34456, 34494, 34532, 34569, 34606, 34642, 34677, 34711, 34743, 34774, 34803, 34832, 34860, 34883, 34902, 34917, 34932, 34947, 34961, 34974, 34985, 34993, 35000, 35006, 35011, 35016, 35020, 35023, 35025, 35027, 35029, 35031, 35033, 35035, 35037, 35039, 35041, 35043, 35045, 35046, 35047, 35048, 35049, 35050, 35051, 35052, 35053, 35054, 35055, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056, 35056]
In [129]:
1000 Prob requests
File "<ipython-input-129-857fafa275e7>", line 1
1000 Prob requests
^
SyntaxError: invalid syntax
In [127]:
lst = list()
for i in range(1000):
t = random.randint(0,10000)
random.seed(t)
nodeSt = randint(0,99)
rate = 0
pardaught = dict()
exclu = list()
connected = list()
queue = [nodeSt]
visited_nodes = set()
vids = sorted([(index,row['Probability']) for index, row in pdf2.iterrows()], key=lambda x: x[1], reverse=True)
t = random.randint(0,10000)
random.seed(t)
temp = randint(0,100)
vid = vids[temp][0]
#print(vid)
path = set()
connected.append(nodeSt)
lst.append(vid)
#lst.append(pdf2.ix[vid,'Probability'])
for node in queue:
if node == nodeSt:
pdf2.ix[vid,'nviews'] += 1
pdf2.ix[vid,'eviews'] += 1
t = random.randint(0,10000)
random.seed(t)
rate = randint(1,5)
r = pdf2.ix[vid,'rating']
pdf2.ix[vid,'rating'] = ((pdf2.ix[vid,'nrating'] * r) + rate)/float(pdf2.ix[vid,'nrating'] + 1)
pdf2.ix[vid,'nrating'] += 1
#print(G.node[node])
neighbors = G.neighbors(node)
#exclu = [n for n in neighbors if n not in visited_nodes]
exclu = [n for n in neighbors if n not in connected]
pardaught[node] = exclu
connected.extend(exclu)
#queue.remove(node)
visited_nodes.add(node)
path.add(node)
queue.extend(exclu)
pdf2.ix[vid,'eviews'] += len(neighbors)
#print(str(node) + " viewed & shared")
else:
for key, values in pardaught.items():
if node in values:
parent = key
if VwR_thr <= (pdf2.ix[vid,'rating']*G.node[node]['ViRt']*G.node[parent]['Attractiveness_Coeff']):
pdf2.ix[vid,'nviews'] += 1
pdf2.ix[vid,'eviews'] += 1
#print(str(node) + " viewed")
rate = randint(1,5)
r = pdf2.ix[vid,'rating']
pdf2.ix[vid,'rating'] = ((pdf2.ix[vid,'nrating'] * r) + rate)/float(pdf2.ix[vid,'nrating'] + 1)
pdf2.ix[vid,'nrating'] += 1
if ShR_thr <= (pdf2.ix[vid,'rating']*G.node[node]['Sharing_Rate']*G.node[parent]['Attractiveness_Coeff']):
#print(G.node[node])
neighbors = G.neighbors(node)
exclu = [n for n in neighbors if n not in connected]
pardaught[node] = exclu
connected.extend(exclu)
#queue.remove(node)
visited_nodes.add(node)
path.add(node)
queue.extend(exclu)
pdf2.ix[vid,'eviews'] += len(neighbors)
#print(str(node) + " shared")
pdf2['Expectation'] = pdf2['eviews'] - pdf2['nviews']
expSum = pdf2['Expectation'].sum()
pdf2['Probability'] = pdf2['Expectation']/float(expSum)
#lst.sort()
#print(lst)
In [125]:
#len(set(lst2))
In [126]:
#diffpdf = pd.DataFrame()
#diffpdf['nviews'] = pdf['nviews'] - df['nviews']
In [127]:
#diffrdf = pd.DataFrame()
#diffrdf['nviews'] = rdf['nviews'] - df['nviews']
In [128]:
#vids2pdf = sorted([(index,row['nviews']) for index, row in pdf.iterrows()], key=lambda x: x[1], reverse=True)
#vids2rdf = sorted([(index,row['nviews']) for index, row in rdf.iterrows()], key=lambda x: x[1], reverse=True)
In [129]:
#lst2pdf = [b for a,b in vids2pdf]
#lst2rdf = [b for a,b in vids2rdf]
In [130]:
#plt.plot(krange,lst2pdf)
#plt.xlabel('Rank')
#plt.ylabel('Number of views')
In [131]:
#plt.plot(krange,lst2rdf)
#plt.xlabel('Rank')
#plt.ylabel('Number of views')
In [132]:
#print(vidsdf)
In [133]:
#print(vidspdf)
In [134]:
#print(vidsrdf)
In [135]:
#plt.plot(lstpdf, krange)
#plt.xlabel('Number of views')
#plt.ylabel('Rank')
In [ ]:
Content source: SubhankarGhosh/NetworkX
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