In [1]:

    

from configparser import ConfigParser
from os.path import join
from os import pardir


    

In [2]:

    

config = ConfigParser()
config.read(join(pardir,'src','credentials.ini'))


    

    
Out[2]:





['../src/credentials.ini']

In [3]:

    

APP_KEY = config['twitter']['app_key']
APP_SECRET = config['twitter']['app_secret']
OAUTH_TOKEN =  config['twitter']['oauth_token']
OAUTH_TOKEN_SECRET =  config['twitter']['oauth_token_secret']


    

In [4]:

    

from twitter import oauth, Twitter, TwitterHTTPError


    

In [5]:

    

auth = oauth.OAuth(OAUTH_TOKEN, OAUTH_TOKEN_SECRET,
                   APP_KEY, APP_SECRET)

twitter_api = Twitter(auth=auth)
twitter_api.retry = True


    

In [6]:

    

tweet = twitter_api.statuses.show(_id='628949369883000832')


    

In [7]:

    

tweet['text']


    

    
Out[7]:





"dear @Microsoft the newOoffice for Mac is great and all, but no Lync update? C'mon."

In [8]:

    

femfreq_tweet_search = twitter_api.statuses.user_timeline(screen_name="femfreq", count=100)


    

In [9]:

    

femfreq_tweet_search[0]['user']['description']


    

    
Out[9]:





'Feminist Frequency is an educational nonprofit working for a more equitable media landscape and online world. Created by Anita Sarkeesian.'

In [10]:

    

femfreq_tweet_search[-1]['text']


    

    
Out[10]:





"Time is running out! Just 4 days left to back Ordinary Women, it doesn't happen without you! https://t.co/gWbfnMQOcp https://t.co/3FJIs5Bozy"

In [11]:

    

tweets = twitter_api.search.tweets(q="#feminazi", count=100)


    

In [12]:

    

tweets['search_metadata']


    

    
Out[12]:





{'completed_in': 0.121,
 'count': 100,
 'max_id': 723548002791510017,
 'max_id_str': '723548002791510017',
 'next_results': '?max_id=722730474121084927&q=%23feminazi&count=100&include_entities=1',
 'query': '%23feminazi',
 'refresh_url': '?since_id=723548002791510017&q=%23feminazi&include_entities=1',
 'since_id': 0,
 'since_id_str': '0'}

In [13]:

    

import pandas as pd

text_gathered = [tweet_data['text'] for tweet_data in tweets['statuses']]
num_tweets = len(text_gathered)
pd_tweets = pd.DataFrame( {'tweet_text': text_gathered,
                           'troll_tag': [False] * num_tweets})


    

In [14]:

    

pd_tweets.head()


    

    
Out[14]:






  

    

      

      
troll_tag
      
tweet_text
    
  
  

    

      
0
      
False
      
@1800flowers Ads pay 4 Limbaugh to call us str...
    
    

      
1
      
False
      
Stop the spread of cultural marxism. #Feminazi...
    
    

      
2
      
False
      
#VivasNosQueremos\n#NantzinVive en mi corazón\...
    
    

      
3
      
False
      
RT @jalgete: Todo es "violencia de género" y "...
    
    

      
4
      
False
      
RT @jalgete: Todo es "violencia de género" y "...
    
  

In [15]:

    

pd_tweets.to_csv('maybe_troll.csv')


    

In [16]:

    

ls


    

    




0. Gather data.ipynb  maybe_troll.csv