In [1]:
from gensim.models import AuthorTopicModel

model = AuthorTopicModel.load('model.atmodel')


C:\ProgramData\Anaconda3\lib\site-packages\gensim\utils.py:860: UserWarning: detected Windows; aliasing chunkize to chunkize_serial
  warnings.warn("detected Windows; aliasing chunkize to chunkize_serial")

In [3]:
model.show_topics(num_topics=10)


Out[3]:
[(18,
  '0.017*"el" + 0.014*"a" + 0.014*"mazo" + 0.013*"paso" + 0.012*"edomex" + 0.011*"ieem" + 0.010*"gobernador" + 0.009*"elección" + 0.009*"pan" + 0.007*"Del Mazo"'),
 (12,
  '0.026*"columna" + 0.010*"enlared" + 0.007*"vía" + 0.005*"venezuela" + 0.005*"fernando" + 0.004*"apoyar" + 0.003*"poesía" + 0.003*"TU VOZ" + 0.003*"notieress" + 0.003*"editor"'),
 (9,
  '0.007*"mesaparatodos" + 0.006*"we" + 0.005*"go" + 0.004*"vocesendirecto" + 0.004*"lipton" + 0.004*"fmi" + 0.004*"David Lipton" + 0.004*"obamacare" + 0.004*"espalda" + 0.004*"still"'),
 (15,
  '0.033*"laprimeramvs" + 0.009*"alaire_laprimeramvs" + 0.008*"yosoitu" + 0.006*"Pascual Castro" + 0.004*"antony" + 0.004*"carbonell" + 0.004*"Cristina Carbonell" + 0.003*"opiniónlsr" + 0.002*"freno" + 0.002*"femenina"'),
 (10,
  '0.015*"enfoque_noticias" + 0.006*"or" + 0.005*"excélsiorinforma" + 0.005*"its" + 0.004*"excélsiorinforma_excélsiortv" + 0.004*"sandoval" + 0.003*"Baja California Sur" + 0.003*"some" + 0.003*"down" + 0.003*"them"'),
 (17,
  '0.019*"despiertaconloret" + 0.018*"enfoque" + 0.016*"lasnoticiascondanielle" + 0.012*"audiontx" + 0.009*"videontx" + 0.007*"alaireconpaola" + 0.004*"interurbano" + 0.004*"vagón" + 0.003*"infografíantx" + 0.003*"dañan"'),
 (1,
  '0.081*"a" + 0.039*"y" + 0.022*"el" + 0.015*"méxico" + 0.009*"mil" + 0.008*"entérate" + 0.007*"cdmx" + 0.007*"años" + 0.006*"gobierno" + 0.005*"video"'),
 (5,
  '0.042*"the" + 0.033*"a" + 0.025*"to" + 0.023*"of" + 0.019*"in" + 0.014*"and" + 0.012*"is" + 0.009*"trump" + 0.008*"for" + 0.008*"it"'),
 (0,
  '0.038*"pri" + 0.017*"el_pri" + 0.017*"columna" + 0.016*"asamblea" + 0.013*"y" + 0.010*"epn" + 0.010*"el" + 0.009*"a" + 0.008*"escribe" + 0.007*"candados"'),
 (16,
  '0.075*"a" + 0.040*"el" + 0.036*"y" + 0.010*"video" + 0.008*"trump" + 0.008*"méxico" + 0.007*"norte" + 0.007*"eu" + 0.006*"corea" + 0.006*"corea_el"')]

In [4]:
aut_top = {}
for key, value in model.id2author.items():
    aut_top[value] = model.get_author_topics(value)

In [5]:
aut_top


Out[5]:
{'ADNPolitico': [(16, 0.99929650810007709)],
 'ActualidadRT': [(16, 0.99971426158086563)],
 'Adela_Micha': [(2, 0.99550011550942041)],
 'Amsalazar': [(2, 0.99311653655557697)],
 'AnaPOrdorica': [(18, 0.99702327433593396)],
 'AristeguiOnline': [(7, 0.99960485729453841)],
 'AztecaNoticias': [(14, 0.99873227708280488)],
 'Canal22': [(2, 0.99910215267298641)],
 'CanalOnceTV': [(6, 0.9981340187304123)],
 'CarlosLoret': [(17, 0.99050695173763437)],
 'CiroGomezL': [(5, 0.99896284724184703)],
 'DeniseDresserG': [(5, 0.99878556471165814)],
 'DeniseMaerker': [(2, 0.99920302349447487)],
 'DiegoEOsorno': [(0, 0.14999666910894646),
  (8, 0.14999705419968132),
  (13, 0.14999719492515337),
  (15, 0.14999708595593339),
  (16, 0.29285363591085511)],
 'E_Q_': [(1, 0.091824800570482673),
  (2, 0.027273594297190385),
  (6, 0.21067892517508072),
  (7, 0.3797903686329398),
  (14, 0.034884057604243242),
  (16, 0.1832342347084242),
  (19, 0.055287684101352895)],
 'EfektoNoticias': [(1, 0.18564323882958397),
  (2, 0.059747015749215204),
  (3, 0.052717737469838093),
  (5, 0.060055718837340732),
  (6, 0.047198422272772475),
  (7, 0.11864437114851543),
  (14, 0.027438953267363394),
  (16, 0.12488245997421815),
  (18, 0.014906303380322698),
  (19, 0.30374408679219189)],
 'EjeCentral': [(1, 0.099923812102874557),
  (2, 0.072537967905715872),
  (3, 0.02018708686409101),
  (7, 0.24358821950672793),
  (14, 0.089549682303683778),
  (16, 0.1926993222004485),
  (18, 0.01835065152165568),
  (19, 0.25660648207470027)],
 'ElFinanciero_Mx': [(1, 0.10284949996232538),
  (2, 0.047218000045037553),
  (5, 0.094117373336345206),
  (7, 0.10651024581189231),
  (14, 0.039770714841465167),
  (16, 0.26860707276130191),
  (18, 0.019773139745941772),
  (19, 0.30191493391257612)],
 'ElHuffPost': [(0, 0.013029119956858366),
  (1, 0.04173357809330714),
  (2, 0.01158952274738256),
  (6, 0.029619624539321016),
  (7, 0.16052413413983277),
  (12, 0.017103355813380537),
  (14, 0.037829954623840499),
  (16, 0.28740297206507487),
  (19, 0.39209494018810975)],
 'El_Universal_Mx': [(1, 0.18557445068496289),
  (2, 0.2052159755448105),
  (3, 0.025287528102209706),
  (5, 0.084258796216968315),
  (6, 0.022831236116206386),
  (7, 0.084497565673614439),
  (10, 0.19297688395939072),
  (14, 0.022579665923064825),
  (16, 0.11088384771702896),
  (18, 0.065162022861669527)],
 'EnfoqueNoticias': [(1, 0.10940968718950568),
  (2, 0.037776054276459609),
  (5, 0.017415066279582645),
  (6, 0.055538644686016922),
  (7, 0.24852310174610975),
  (10, 0.20875023876853807),
  (14, 0.018977081248131727),
  (16, 0.085205909518182382),
  (17, 0.10359801975069677),
  (18, 0.10888885028236259)],
 'Excelsior': [(1, 0.042391685457805792),
  (2, 0.21894115162664601),
  (5, 0.034026528530283498),
  (6, 0.11374685175014522),
  (7, 0.22873211743347491),
  (10, 0.066561483475176181),
  (14, 0.042586851700056876),
  (16, 0.14387484615920879),
  (18, 0.10756994365962426)],
 'ExpansionMx': [(0, 0.010985314507198073),
  (1, 0.15776948053720261),
  (2, 0.093184084898080305),
  (3, 0.055739324695470265),
  (6, 0.036034096738034038),
  (7, 0.10891942117424119),
  (14, 0.059622950957282012),
  (16, 0.45955953579263431),
  (17, 0.011542149040730901)],
 'FedericoArreola': [(0, 0.17422079722808836),
  (1, 0.020172099856251215),
  (2, 0.12058514150001849),
  (3, 0.11641414846297417),
  (5, 0.01735291188676311),
  (6, 0.23040459465377786),
  (7, 0.15163104565847901),
  (14, 0.094863726879767504),
  (16, 0.072402828859375809)],
 'FernandoDworak': [(0, 0.034256824764461596),
  (1, 0.12177247180388244),
  (2, 0.087165957242482106),
  (5, 0.1008565823275456),
  (6, 0.022728773606036763),
  (7, 0.077247474887853926),
  (11, 0.1897854465630687),
  (14, 0.015991851157370757),
  (16, 0.33790813642106843)],
 'Foro_TV': [(0, 0.012977926154936807),
  (1, 0.20978968085162966),
  (2, 0.24445957785524441),
  (4, 0.094552672047578015),
  (6, 0.0259479116193751),
  (7, 0.19690488042082549),
  (14, 0.020613673780226757),
  (16, 0.078207624295753342),
  (18, 0.061350314070729092),
  (19, 0.03602315730797042)],
 'Imagen_Mx': [(1, 0.12492261532867097),
  (2, 0.062536490929950866),
  (4, 0.32573940500427379),
  (6, 0.28018557722987425),
  (7, 0.048369107503186612),
  (16, 0.079133805102336946),
  (19, 0.070545664791315937)],
 'J_Fdz_Menendez': [(0, 0.15448920063933155),
  (1, 0.031473664268349744),
  (2, 0.26728489183186732),
  (5, 0.061335091715856598),
  (6, 0.020984307724039954),
  (7, 0.03821745124920968),
  (14, 0.012132115409068863),
  (16, 0.38448589331043431)],
 'JavierSolorzano': [(0, 0.068158793965872044),
  (1, 0.031798818203748677),
  (2, 0.23374230628849468),
  (5, 0.06263614640546343),
  (6, 0.22811381969844047),
  (7, 0.14942822468751876),
  (11, 0.1106967037167837),
  (14, 0.078725170113893544),
  (16, 0.033873176305158445)],
 'JohnMAckerman': [(2, 0.042795291263658573),
  (4, 0.081947705362074449),
  (5, 0.047243129546055786),
  (6, 0.077156276346078523),
  (7, 0.13340361184239513),
  (8, 0.053209020010714404),
  (14, 0.078848678997669883),
  (16, 0.23498722938618968),
  (18, 0.24133642127101895)],
 'JoseCardenas1': [(0, 0.071239857537134035),
  (1, 0.087739778609409),
  (2, 0.048054056960719981),
  (5, 0.076738746577094022),
  (6, 0.015789681397042274),
  (7, 0.25163466154980452),
  (14, 0.10702276895246937),
  (16, 0.18016446153522891),
  (18, 0.15271753826502102)],
 'LaRazon_mx': [(0, 0.011952749577630933),
  (1, 0.21598438972660014),
  (2, 0.059332994926205862),
  (3, 0.04683779264809057),
  (5, 0.017230470197783569),
  (6, 0.029591479480798089),
  (7, 0.32635955735642769),
  (13, 0.013769167541925042),
  (14, 0.09832999586001355),
  (15, 0.031783094803180728),
  (16, 0.12378032527344533),
  (17, 0.015041188887813218)],
 'LeonKrauze': [(1, 0.02652331743601169),
  (2, 0.047796744596468897),
  (3, 0.034528950624640883),
  (5, 0.35587840800614412),
  (6, 0.037664015080410881),
  (7, 0.02779139970694702),
  (14, 0.014561537845041017),
  (15, 0.25082092309933396),
  (16, 0.17593101629964467),
  (19, 0.012328445932080897)],
 'LeonardoCurzio': [(0, 0.078867340234902703),
  (1, 0.16806599335411238),
  (2, 0.031789302685637691),
  (5, 0.14731862527325557),
  (6, 0.018033924693447962),
  (7, 0.1787871505624625),
  (12, 0.13221257509339648),
  (16, 0.1699902450849948),
  (18, 0.061389518848548388)],
 'LuisCardenasMx': [(1, 0.11691145898612866),
  (2, 0.031836286866428247),
  (5, 0.038408424594382547),
  (6, 0.29303028206234011),
  (7, 0.2016633161208467),
  (14, 0.011964135651671088),
  (15, 0.1859111389501274),
  (16, 0.10740736644087386),
  (18, 0.010975894896860476)],
 'MarioBeteta': [(0, 0.088532660636570767),
  (1, 0.085087414279801737),
  (2, 0.054956783653605179),
  (5, 0.10074861356160164),
  (6, 0.2025093744570643),
  (7, 0.29077245582170835),
  (14, 0.036555058899941976),
  (16, 0.10765941190322123),
  (18, 0.032174784158232113)],
 'MexicanTimes': [(1, 0.18263841909926226),
  (2, 0.10534936827333828),
  (3, 0.057108809069698847),
  (5, 0.050204126021387872),
  (6, 0.044342971311795425),
  (7, 0.090715139978320106),
  (14, 0.065343530572233466),
  (15, 0.060874028425340114),
  (16, 0.22906394183837586),
  (18, 0.067175514713026907),
  (19, 0.045373048602784911)],
 'Milenio': [(0, 0.022840662271347061),
  (1, 0.11232384859180033),
  (2, 0.041650671622116699),
  (5, 0.011893786253351716),
  (7, 0.087418317037074991),
  (12, 0.011837045043243562),
  (13, 0.010202783984973341),
  (14, 0.39011236944929462),
  (16, 0.16236418669092434),
  (18, 0.040866544592756918),
  (19, 0.098572701642200888)],
 'NTelevisa_com': [(1, 0.1196202172095821),
  (2, 0.075854549185688236),
  (5, 0.043776805649850578),
  (6, 0.069177861132451973),
  (7, 0.10504547840277238),
  (14, 0.053632566156120894),
  (16, 0.25725533825836405),
  (17, 0.087909331943413244),
  (18, 0.16622501742520868),
  (19, 0.020986517378956942)],
 'NoticiasMVS': [(0, 0.02782512976586678),
  (1, 0.08705985006385622),
  (2, 0.12591172186934843),
  (5, 0.011678127836325417),
  (6, 0.16287205335794314),
  (7, 0.27985587140224966),
  (9, 0.062102821289151566),
  (13, 0.030698248996255201),
  (14, 0.033776669347100045),
  (16, 0.10320951862678565),
  (18, 0.074331164800611124)],
 'Notimex': [(1, 0.13765539468416138),
  (2, 0.13370829680318322),
  (5, 0.043447884832275012),
  (6, 0.092593253544827642),
  (7, 0.17132534560682416),
  (13, 0.076342197373044041),
  (14, 0.17860492694808572),
  (16, 0.06131863623158549),
  (17, 0.044888675180336832),
  (18, 0.012618449394744101),
  (19, 0.034030771413404631)],
 'PPmerino': [(0, 0.041330954998126272),
  (1, 0.12543367991625842),
  (2, 0.063618504469708459),
  (5, 0.13873555474613117),
  (6, 0.027462735031499787),
  (7, 0.091811718171128556),
  (10, 0.014914948425274452),
  (11, 0.19798085247409755),
  (14, 0.01735552164116452),
  (16, 0.16355359015918591),
  (18, 0.043034528259854411),
  (19, 0.063754404167081266)],
 'PabloHiriart': [(0, 0.1726553955608788),
  (1, 0.1068726104707641),
  (2, 0.047983282616022353),
  (3, 0.011632421966915921),
  (7, 0.10599595860971901),
  (12, 0.28603341568629809),
  (14, 0.034568326262259336),
  (16, 0.084916676610737304),
  (18, 0.052792468339018413),
  (19, 0.08683003205186382)],
 'Pajaropolitico': [(1, 0.20923628323173873),
  (2, 0.056202016669082748),
  (3, 0.01639123420491485),
  (5, 0.011740200790682451),
  (6, 0.044417258187482107),
  (7, 0.088127602304113442),
  (10, 0.1135111176619579),
  (14, 0.068932786088289941),
  (16, 0.19371950042628786),
  (17, 0.04779253736198627),
  (18, 0.066497310531997839),
  (19, 0.072151179767824578)],
 'PaolaRojas': [(1, 0.28229873505725167),
  (2, 0.1817616891370423),
  (5, 0.034926867114397853),
  (7, 0.24899869683534961),
  (14, 0.072348955879563137),
  (16, 0.097774936589986386),
  (17, 0.03277090801626785),
  (18, 0.027173710839664047),
  (19, 0.013066038030222826)],
 'PedroFerriz': [(1, 0.15796273069950323),
  (2, 0.079052174611240714),
  (5, 0.069799926763503314),
  (6, 0.23651213327308812),
  (11, 0.22497325272719082),
  (14, 0.020417098049440932),
  (16, 0.17387827736777589)],
 'Pizu': [(0, 0.080696386662442304),
  (1, 0.11698957565925475),
  (2, 0.17530310653386078),
  (5, 0.069204659535816462),
  (6, 0.17103371407207243),
  (9, 0.32240991150704057),
  (19, 0.045303749100535765)],
 'PublimetroMX': [(1, 0.11281121543738669),
  (2, 0.11340993293715952),
  (6, 0.054534357188620326),
  (7, 0.17886493131299674),
  (9, 0.021425817878681478),
  (14, 0.21371540947602566),
  (16, 0.12525835275986921),
  (17, 0.018034322952922104),
  (18, 0.067097823665911813),
  (19, 0.080410022139770249)],
 'Radio_Formula': [(0, 0.14189431513493572),
  (1, 0.078532622190870066),
  (2, 0.047234030327009381),
  (5, 0.09707693926339156),
  (6, 0.28959100827458678),
  (7, 0.15840459399575077),
  (16, 0.088622912699139009),
  (18, 0.057007493241100951),
  (19, 0.013669182693836376)],
 'Reforma': [(1, 0.11126292477314706),
  (2, 0.084566294417128637),
  (5, 0.039446667591026149),
  (6, 0.029281503839449823),
  (7, 0.1516850124634806),
  (11, 0.11283254396852876),
  (14, 0.04586682126085663),
  (16, 0.26389083189634943),
  (18, 0.1395341153866039)],
 'Reporte_Indigo': [(1, 0.30462511839115253),
  (2, 0.11015114658287178),
  (5, 0.015795282986989109),
  (6, 0.02382610072172214),
  (7, 0.074792721888792796),
  (8, 0.18393480500379994),
  (14, 0.0327468827860872),
  (16, 0.12320293863951982),
  (18, 0.023227771279157271),
  (19, 0.096976122890637909)],
 'RicardoAlemanMx': [(0, 0.13218652314585935),
  (1, 0.094581724131744205),
  (2, 0.15311694836419734),
  (5, 0.063545737475707492),
  (6, 0.042469306419974012),
  (7, 0.11309635187137826),
  (8, 0.25029695712803679),
  (10, 0.025356597429445016),
  (14, 0.032900421857603571),
  (16, 0.06556827021657953),
  (19, 0.017141834619744882)],
 'RoyCampos': [(0, 0.028839709040845148),
  (1, 0.10869728930309613),
  (2, 0.096556263722137367),
  (3, 0.10197875013141056),
  (5, 0.024662504564460452),
  (6, 0.052705697830042815),
  (7, 0.12123002341060023),
  (9, 0.16696352340334031),
  (14, 0.031448914137353089),
  (16, 0.10925236454904015),
  (19, 0.156086395694705)],
 'SGarciaSoto': [(0, 0.36152276290195096),
  (1, 0.015006645509582301),
  (2, 0.13398787064931877),
  (5, 0.022102949412786958),
  (6, 0.15425808119217588),
  (7, 0.13163220188006433),
  (16, 0.061298042926188241),
  (18, 0.098773768629298861),
  (19, 0.017477191730095036)],
 'SalCamarena': [(0, 0.22392393926389059),
  (1, 0.064140446250543298),
  (2, 0.025736089391026822),
  (3, 0.027757831496481509),
  (5, 0.0617714597775001),
  (6, 0.098295507938644028),
  (7, 0.09071330201346868),
  (8, 0.016318342079668011),
  (14, 0.12212025018371986),
  (18, 0.21089665580223707),
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  (7, 0.032057023947538961),
  (8, 0.3588865513879928),
  (16, 0.11240817135968408),
  (17, 0.022309511117440162),
  (18, 0.041507057014081757),
  (19, 0.024836874667332535)]}

In [6]:
%%time
from sklearn.manifold import TSNE
tsne = TSNE(n_components=2, random_state=0)
smallest_author = 0  # Ignore authors with documents less than this.
authors = [model.author2id[a] for a in model.author2id.keys() if len(model.author2doc[a]) >= smallest_author]
_ = tsne.fit_transform(model.state.gamma[authors, :])  # Result stored in tsne.embedding_


Wall time: 1.19 s

In [ ]:
from bokeh.io import output_file
output_file('grafica.html')

In [ ]:
from bokeh.models import HoverTool
from bokeh.plotting import figure, show, ColumnDataSource

x = tsne.embedding_[:, 0]
y = tsne.embedding_[:, 1]
author_names = [model.id2author[a] for a in authors]

scale = 0.01
author_sizes = [len(model.author2doc[a]) for a in author_names]
radii = [size * scale for size in author_sizes]

source = ColumnDataSource(
        data=dict(
            x=x,
            y=y,
            author_names=author_names,
            author_sizes=author_sizes,
            radii=radii,
        )
    )

hover = HoverTool(
        tooltips=[
        ("author", "@author_names"),
        ("size", "@author_sizes"),
        ]
    )

p = figure(tools=[hover, 'crosshair,pan,wheel_zoom,box_zoom,reset,save,lasso_select'])
p.scatter('x', 'y', radius='radii', source=source, fill_alpha=0.6, line_color=None)
show(p)

In [ ]:
from gensim.similarities import MatrixSimilarity


index = MatrixSimilarity(model[list(model.id2author.values())])

In [ ]:
from gensim import matutils
import pandas as pd


author_vecs = [model.get_author_topics(author) for author in model.id2author.values()]

def similarity(vec1, vec2):
    dist = matutils.hellinger(matutils.sparse2full(vec1, model.num_topics), \
                              matutils.sparse2full(vec2, model.num_topics))
    sim = 1.0 / (1.0 + dist)
    return sim

def get_sims(vec):
    sims = [similarity(vec, vec2) for vec2 in author_vecs]
    return sims

def get_table(name, top_n=10, smallest_author=1):
    sims = get_sims(model.get_author_topics(name))


    table = []
    for elem in enumerate(sims):
        author_name = model.id2author[elem[0]]
        sim = elem[1]
        author_size = len(model.author2doc[author_name])
        if author_size >= smallest_author:
            table.append((author_name, sim, author_size))
            

    df = pd.DataFrame(table, columns=['Author', 'Score', 'Size'])
    df = df.sort_values('Score', ascending=False)[:top_n]
    
    return df

In [ ]:
get_table('Pajaropolitico',top_n=136)

In [ ]:
import pickle
dictionary = pickle.load(open("dictionary.p", "rb"))

In [ ]:
import pyLDAvis.gensim
pyLDAvis.enable_notebook()

In [ ]:
pyLDAvis.gensim.prepare(model, model.corpus,dictionary)

In [ ]: