Structural Topic Modelling on Gender in Sports News

MekhalaKumar

Olympics2020

GenderandSports

StructuralTopicModelling

BlogPost5

Author

Mekhala Kumar

Published

December 15, 2022

In this post, I conducted Structural Topic Modelling with the help of the stm package.

library(tidyverse)
library(quanteda)
library(readtext)
library(striprtf)
library(corpustools)
library(quanteda.textplots)
library(readr)
library(topicmodels)
library(tidytext)
library(dplyr)
library(ggplot2)
library(tidyr)
library(tm)
library(stm)

Reading in the dataset

I had to make a few changes to the dataset to use it for structural topic modelling, so I read in the data file that was present without preprocessing and repeated preprocessing after modifying the data.

dfnews<- readRDS(file = "_data/CleanData.rds")

Tidying and modifying the dataset

In order to use structural topic modelling, I required a variable that I could use for prevalence. Since my research question was to check for gender bias in newspapers, using the Tags metadata, I created a new column which classified the article as related to women’s sports or men’s sports. Since the Tags included multiple categories, I checked whether each row had the term MEN’S SPORTS or WOMEN’S SPORTS. I faced an issue while filtering out as while using regular expressions, the tags with ‘women’ were also removed when I was trying to remove only the tags with ‘men’. Hence, I first replaced the term Women’s with Nari (Hindi word for woman) in order to avoid filtering errors due to regular expressions.

dfnews_edit <- dfnews %>% 
  mutate_at(c('Tags'),funs(str_replace(., "WOMEN'S", "NARI")))

Warning: `funs()` was deprecated in dplyr 0.8.0.
ℹ Please use a list of either functions or lambdas:

# Simple named list: list(mean = mean, median = median)

# Auto named with `tibble::lst()`: tibble::lst(mean, median)

# Using lambdas list(~ mean(., trim = .2), ~ median(., na.rm = TRUE))

#Women's sports - removes all the tags which have the word men's and then looks for all the columns that have the word women
 woman <- dfnews_edit %>% 
   filter(!grepl("MEN'S", Tags))%>%
    filter(grepl("NARI", Tags))
 #woman
 
wom1<-woman%>%
  mutate(Classification="Women")
#wom1
dim(wom1)

[1] 289   5

#Men's sports
men <- dfnews_edit %>% 
   filter(!grepl("NARI", Tags))%>%
    filter(grepl("MEN'S", Tags))
#men
men1<-men%>%
  mutate(Classification="Men")
#men1
dim(men1)

[1] 198   5

#Men's sports and women's sports combined
both<-dfnews_edit%>%
  filter(grepl("MEN'S.*NARI|NARI.*MEN'S", Tags))
#both
dim(both)

[1] 149   4

both<-both%>%
  mutate(Classification="MenAndWomen")
#both

#sanity check
remaining<-dfnews_edit %>% 
   filter(!grepl("NARI|MEN'S|MEN'S.*NARI|NARI.*MEN'S", Tags))
#remaining
dim(remaining)

[1] 521   4

Creation of dataset to be used for structural topic modelling

There were some observations which contained metadata pertaining to both men’s and women’s sports. However, since I wanted to analyse whether there were differences between the aspects covered in sports for men and women, I did not keep the observations which had both the tags. I also realised that some of the articles were repeated so I filtered out the duplicates. With these changes, the dataset was reduced to 468 articles.

dim(both)

[1] 149   5

both1<-both %>% distinct(body, .keep_all = TRUE)
dim(both1)

[1] 148   5

df_with3<-rbind(wom1,men1,both)
dim(df_with3)

[1] 636   5

df_with3<-df_with3%>%
          select(!Tags)
df_with3<-df_with3 %>% distinct(body, .keep_all = TRUE)
dim(df_with3)

[1] 616   4

#saveRDS(df_with3, file = "Data/FilesClassification.rds")
#saveRDS(df_with3, file = "Data/FilesClassificationNoDuplicates.rds")

df_final<-rbind(wom1,men1)
df_final<-df_final%>%
          select(!Tags)
dim(df_final)

[1] 487   4

df_final<-df_final %>% distinct(body, .keep_all = TRUE)
dim(df_final)

[1] 468   4

Preprocessing

The same steps as done in previous blog posts were conducted for preprocessing. # Creating the corpus

#Converting to corpus
newspaper_corpus <- corpus(df_final,text_field = "body")
head(newspaper_corpus)

Corpus consisting of 6 documents and 3 docvars.
text1 :
" From a solitary two-day fixture between Great Britain and F..."

text2 :
" Tokyo Olympics Day 10 Full Schedule: Kamalpreet Kaur stunne..."

text3 :
" Haryana CM Manohar Lal Khattar has announced Rs.50 lakh cas..."

text4 :
" India's quest for another medal will continue on Day 8 of t..."

text5 :
" India vs Argentina Women's Hockey Semifinal Match Live Stre..."

text6 :
" India would fancy their chances of a medal finish as they g..."

newspaper_corpus_summary <- summary(newspaper_corpus)
head(newspaper_corpus_summary)

   Text Types Tokens Sentences       newspaper            date Classification
1 text1   260    542        22 Hindustan Times August 9, 2021           Women
2 text2   106    220         5 Hindustan Times August 2, 2021           Women
3 text3   126    298        12 Hindustan Times August 7, 2021           Women
4 text4   168    326         5 Hindustan Times  July 31, 2021           Women
5 text5   104    292        12 Hindustan Times August 4, 2021           Women
6 text6   196    393         6 Hindustan Times  July 30, 2021           Women

newspaper_corpus_summary$Tokens

  [1]  542  220  298  326  292  393  328  305  371  255  780  376  516  207  635
 [16] 1084  321  662  375  353  707  440  294  290  282  282  788  451  483  304
 [31]  637 1362  338  795  433  603  301  717  485  387  633  291  350  466  462
 [46]  290  326  328  224  934 1277 1100  443  868  261  571  786 1219  929  377
 [61]  328  271 1027  375 1203  387  428  859  585  506  501  877  368  368 1072
 [76] 1081  425  428  484  681  772  778  202  636  975 1012  867  888 1075  150
 [91]  153  147  112  173   89  143  164   62  459  286

Checking for metadata, creating tokens, removing punctuation and removing stopwords.

#docvars(newspaper_corpus)

newspaper_tokens <- tokens(newspaper_corpus)
head(newspaper_tokens)

Tokens consisting of 6 documents and 3 docvars.
text1 :
 [1] "From"     "a"        "solitary" "two-day"  "fixture"  "between" 
 [7] "Great"    "Britain"  "and"      "France"   "in"       "the"     
[ ... and 530 more ]

text2 :
 [1] "Tokyo"      "Olympics"   "Day"        "10"         "Full"      
 [6] "Schedule"   ":"          "Kamalpreet" "Kaur"       "stunned"   
[11] "the"        "nation"    
[ ... and 208 more ]

text3 :
 [1] "Haryana"   "CM"        "Manohar"   "Lal"       "Khattar"   "has"      
 [7] "announced" "Rs"        "."         "50"        "lakh"      "cash"     
[ ... and 286 more ]

text4 :
 [1] "India's"  "quest"    "for"      "another"  "medal"    "will"    
 [7] "continue" "on"       "Day"      "8"        "of"       "the"     
[ ... and 314 more ]

text5 :
 [1] "India"     "vs"        "Argentina" "Women's"   "Hockey"    "Semifinal"
 [7] "Match"     "Live"      "Streaming" ","         "Tokyo"     "Olympics" 
[ ... and 280 more ]

text6 :
 [1] "India"   "would"   "fancy"   "their"   "chances" "of"      "a"      
 [8] "medal"   "finish"  "as"      "they"    "gear"   
[ ... and 381 more ]

newspaper_tokens <- tokens(newspaper_tokens ,
                                    remove_punct = T)
head(newspaper_tokens)

Tokens consisting of 6 documents and 3 docvars.
text1 :
 [1] "From"     "a"        "solitary" "two-day"  "fixture"  "between" 
 [7] "Great"    "Britain"  "and"      "France"   "in"       "the"     
[ ... and 464 more ]

text2 :
 [1] "Tokyo"      "Olympics"   "Day"        "10"         "Full"      
 [6] "Schedule"   "Kamalpreet" "Kaur"       "stunned"    "the"       
[11] "nation"     "with"      
[ ... and 171 more ]

text3 :
 [1] "Haryana"   "CM"        "Manohar"   "Lal"       "Khattar"   "has"      
 [7] "announced" "Rs"        "50"        "lakh"      "cash"      "award"    
[ ... and 253 more ]

text4 :
 [1] "India's"  "quest"    "for"      "another"  "medal"    "will"    
 [7] "continue" "on"       "Day"      "8"        "of"       "the"     
[ ... and 265 more ]

text5 :
 [1] "India"     "vs"        "Argentina" "Women's"   "Hockey"    "Semifinal"
 [7] "Match"     "Live"      "Streaming" "Tokyo"     "Olympics"  "Winning"  
[ ... and 249 more ]

text6 :
 [1] "India"   "would"   "fancy"   "their"   "chances" "of"      "a"      
 [8] "medal"   "finish"  "as"      "they"    "gear"   
[ ... and 317 more ]

withoutstopwords_news<- tokens_select(newspaper_tokens, 
                    pattern = stopwords("en"),
                    select = "remove")
print(withoutstopwords_news)

Tokens consisting of 468 documents and 3 docvars.
text1 :
 [1] "solitary"  "two-day"   "fixture"   "Great"     "Britain"   "France"   
 [7] "1900"      "Olympics"  "prospects" "cricket's" "inclusion" "8-team"   
[ ... and 271 more ]

text2 :
 [1] "Tokyo"      "Olympics"   "Day"        "10"         "Full"      
 [6] "Schedule"   "Kamalpreet" "Kaur"       "stunned"    "nation"    
[11] "64m"        "throw"     
[ ... and 138 more ]

text3 :
 [1] "Haryana"   "CM"        "Manohar"   "Lal"       "Khattar"   "announced"
 [7] "Rs"        "50"        "lakh"      "cash"      "award"     "every"    
[ ... and 155 more ]

text4 :
 [1] "India's"  "quest"    "another"  "medal"    "will"     "continue"
 [7] "Day"      "8"        "Tokyo"    "Olympics" "ace"      "shuttler"
[ ... and 207 more ]

text5 :
 [1] "India"     "vs"        "Argentina" "Women's"   "Hockey"    "Semifinal"
 [7] "Match"     "Live"      "Streaming" "Tokyo"     "Olympics"  "Winning"  
[ ... and 185 more ]

text6 :
 [1] "India"    "fancy"    "chances"  "medal"    "finish"   "gear"    
 [7] "Day"      "7"        "Tokyo"    "Olympics" "eyes"     "archer"  
[ ... and 251 more ]

[ reached max_ndoc ... 462 more documents ]

head(withoutstopwords_news)

Tokens consisting of 6 documents and 3 docvars.
text1 :
 [1] "solitary"  "two-day"   "fixture"   "Great"     "Britain"   "France"   
 [7] "1900"      "Olympics"  "prospects" "cricket's" "inclusion" "8-team"   
[ ... and 271 more ]

text2 :
 [1] "Tokyo"      "Olympics"   "Day"        "10"         "Full"      
 [6] "Schedule"   "Kamalpreet" "Kaur"       "stunned"    "nation"    
[11] "64m"        "throw"     
[ ... and 138 more ]

text3 :
 [1] "Haryana"   "CM"        "Manohar"   "Lal"       "Khattar"   "announced"
 [7] "Rs"        "50"        "lakh"      "cash"      "award"     "every"    
[ ... and 155 more ]

text4 :
 [1] "India's"  "quest"    "another"  "medal"    "will"     "continue"
 [7] "Day"      "8"        "Tokyo"    "Olympics" "ace"      "shuttler"
[ ... and 207 more ]

text5 :
 [1] "India"     "vs"        "Argentina" "Women's"   "Hockey"    "Semifinal"
 [7] "Match"     "Live"      "Streaming" "Tokyo"     "Olympics"  "Winning"  
[ ... and 185 more ]

text6 :
 [1] "India"    "fancy"    "chances"  "medal"    "finish"   "gear"    
 [7] "Day"      "7"        "Tokyo"    "Olympics" "eyes"     "archer"  
[ ... and 251 more ]

#as.character(withoutstopwords_news)

Conversion to document feature matrix

news_dfm_stm <- dfm(tokens(withoutstopwords_news))
news_dfm_stm <- dfm_remove(news_dfm_stm, c("said","also","says","can","just"), verbose = TRUE)

removed 5 features

I recoded the classification to be 1 for Women and 0 for Men to be used as the prevalence for the model.

df_final<- mutate(df_final,Gender=recode(Classification,"Women"="1","Men"="0"))
df_final$Gender<-as.numeric(df_final$Gender)

Choosing K

I selected 25 topics based on the semantic coherence.

differentKs <- searchK(news_dfm_stm,
                       K = c(5, 10,15, 25,50),
                       prevalence = ~ Gender,
                       N = floor(0.1 * 468),
                       data = df_final,
                       max.em.its = 100,
                       init.type = "Spectral")

Beginning Spectral Initialization 
     Calculating the gram matrix...
     Using only 10000 most frequent terms during initialization...
     Finding anchor words...
    .....
     Recovering initialization...
    ....................................................................................................
Initialization complete.
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Topic 1: india, hockey, team, match, olympics 
 Topic 2: olympics, sindhu, tokyo, will, games 
 Topic 3: olympics, women's, round, team, indian 
 Topic 4: hockey, team, indian, india, olympics 
 Topic 5: medal, olympics, tokyo, sports, india 
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Topic 1: india, hockey, team, match, olympics 
 Topic 2: olympics, sindhu, tokyo, will, games 
 Topic 3: olympics, round, women's, indian, world 
 Topic 4: hockey, team, indian, olympics, india 
 Topic 5: medal, olympics, tokyo, sports, india 
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Topic 1: india, hockey, team, match, olympics 
 Topic 2: olympics, sindhu, tokyo, will, games 
 Topic 3: olympics, round, women's, world, indian 
 Topic 4: hockey, team, indian, olympics, india 
 Topic 5: medal, olympics, tokyo, sports, india 
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Topic 1: india, hockey, team, match, olympics 
 Topic 2: olympics, tokyo, sindhu, will, games 
 Topic 3: olympics, round, women's, world, indian 
 Topic 4: hockey, team, indian, olympics, india 
 Topic 5: medal, olympics, tokyo, india, sports 
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Topic 1: india, hockey, team, match, olympics 
 Topic 2: olympics, tokyo, sindhu, will, games 
 Topic 3: olympics, round, women's, indian, world 
 Topic 4: hockey, team, indian, olympics, india 
 Topic 5: medal, olympics, tokyo, india, sports 
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Topic 1: india, hockey, team, match, olympics 
 Topic 2: olympics, tokyo, sindhu, will, games 
 Topic 3: olympics, round, women's, indian, world 
 Topic 4: hockey, team, indian, olympics, india 
 Topic 5: medal, olympics, tokyo, india, sports 
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Model Converged 
Beginning Spectral Initialization 
     Calculating the gram matrix...
     Using only 10000 most frequent terms during initialization...
     Finding anchor words...
    ..........
     Recovering initialization...
    ....................................................................................................
Initialization complete.
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Topic 1: india, hockey, match, team, olympics 
 Topic 2: tokyo, tennis, world, games, will 
 Topic 3: round, olympics, men's, team, indian 
 Topic 4: hockey, team, women's, indian, india 
 Topic 5: mirabai, sports, tokyo, medal, olympics 
 Topic 6: hockey, team, medal, singh, indian 
 Topic 7: olympics, medal, sindhu, tokyo, gold 
 Topic 8: medal, olympic, aditi, borgohain, olympics 
 Topic 9: team, hockey, women, olympics, two 
 Topic 10: hockey, team, olympics, players, singh 
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Topic 1: india, match, hockey, team, olympics 
 Topic 2: tokyo, tennis, world, games, will 
 Topic 3: round, men's, olympics, team, indian 
 Topic 4: hockey, team, indian, women's, india 
 Topic 5: mirabai, sports, tokyo, olympics, medal 
 Topic 6: hockey, team, medal, singh, indian 
 Topic 7: olympics, medal, sindhu, tokyo, gold 
 Topic 8: medal, borgohain, aditi, olympic, olympics 
 Topic 9: team, hockey, women, olympics, family 
 Topic 10: hockey, team, olympics, players, singh 
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Topic 1: india, match, hockey, team, olympics 
 Topic 2: tokyo, tennis, world, games, will 
 Topic 3: round, men's, olympics, team, indian 
 Topic 4: hockey, team, indian, women's, india 
 Topic 5: mirabai, sports, olympics, tokyo, medal 
 Topic 6: hockey, team, medal, singh, indian 
 Topic 7: olympics, medal, sindhu, tokyo, gold 
 Topic 8: medal, borgohain, aditi, olympic, olympics 
 Topic 9: team, hockey, women, olympics, family 
 Topic 10: hockey, team, olympics, players, indian 
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Completing Iteration 16 (approx. per word bound = -7.192, relative change = 5.653e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 17 (approx. per word bound = -7.191, relative change = 6.311e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 18 (approx. per word bound = -7.191, relative change = 4.588e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 19 (approx. per word bound = -7.191, relative change = 2.917e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 20 (approx. per word bound = -7.191, relative change = 2.325e-05) 
Topic 1: india, match, hockey, team, olympics 
 Topic 2: tokyo, tennis, world, games, will 
 Topic 3: round, men's, olympics, team, indian 
 Topic 4: hockey, team, indian, women's, india 
 Topic 5: mirabai, sports, olympics, tokyo, medal 
 Topic 6: hockey, team, medal, singh, indian 
 Topic 7: olympics, medal, sindhu, tokyo, gold 
 Topic 8: medal, borgohain, aditi, olympic, olympics 
 Topic 9: team, hockey, women, olympics, family 
 Topic 10: hockey, team, players, olympics, medal 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 21 (approx. per word bound = -7.190, relative change = 2.475e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 22 (approx. per word bound = -7.190, relative change = 1.992e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 23 (approx. per word bound = -7.190, relative change = 1.586e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 24 (approx. per word bound = -7.190, relative change = 2.059e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 25 (approx. per word bound = -7.190, relative change = 2.522e-05) 
Topic 1: india, match, hockey, team, olympics 
 Topic 2: tokyo, tennis, world, games, will 
 Topic 3: round, olympics, men's, team, indian 
 Topic 4: hockey, team, women's, indian, india 
 Topic 5: mirabai, sports, olympics, tokyo, medal 
 Topic 6: hockey, team, medal, singh, indian 
 Topic 7: olympics, medal, sindhu, tokyo, gold 
 Topic 8: medal, borgohain, aditi, olympic, olympics 
 Topic 9: team, hockey, women, olympics, family 
 Topic 10: hockey, team, olympics, players, medal 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 26 (approx. per word bound = -7.190, relative change = 2.475e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 27 (approx. per word bound = -7.189, relative change = 1.853e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 28 (approx. per word bound = -7.189, relative change = 1.586e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 29 (approx. per word bound = -7.189, relative change = 1.889e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 30 (approx. per word bound = -7.189, relative change = 2.096e-05) 
Topic 1: india, match, hockey, team, olympics 
 Topic 2: tokyo, tennis, world, games, will 
 Topic 3: round, olympics, men's, team, indian 
 Topic 4: hockey, team, indian, women's, india 
 Topic 5: mirabai, sports, olympics, tokyo, medal 
 Topic 6: hockey, team, medal, singh, indian 
 Topic 7: olympics, medal, sindhu, tokyo, gold 
 Topic 8: medal, borgohain, aditi, olympic, olympics 
 Topic 9: team, hockey, women, olympics, family 
 Topic 10: hockey, team, olympics, players, medal 
.....................................................................................................................
Completed E-Step (0 seconds). 
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Completing Iteration 31 (approx. per word bound = -7.189, relative change = 2.038e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 32 (approx. per word bound = -7.189, relative change = 1.734e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 33 (approx. per word bound = -7.189, relative change = 1.193e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Model Converged 
Beginning Spectral Initialization 
     Calculating the gram matrix...
     Using only 10000 most frequent terms during initialization...
     Finding anchor words...
    ...............
     Recovering initialization...
    ....................................................................................................
Initialization complete.
.....................................................................................................................
Completed E-Step (0 seconds). 
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Completing Iteration 1 (approx. per word bound = -7.851) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 2 (approx. per word bound = -7.111, relative change = 9.426e-02) 
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Completed E-Step (0 seconds). 
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Completing Iteration 3 (approx. per word bound = -7.055, relative change = 7.887e-03) 
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Completed E-Step (0 seconds). 
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Completing Iteration 4 (approx. per word bound = -7.041, relative change = 2.001e-03) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 5 (approx. per word bound = -7.035, relative change = 8.212e-04) 
Topic 1: india, hockey, match, olympics, will 
 Topic 2: indian, will, tennis, tokyo, games 
 Topic 3: women's, round, men's, olympics, will 
 Topic 4: team, hockey, women's, indian, india 
 Topic 5: sports, olympics, athletes, india, tokyo 
 Topic 6: team, india, hockey, singh, medal 
 Topic 7: sindhu, olympics, medal, tokyo, bronze 
 Topic 8: aditi, us, olympics, golf, medal 
 Topic 9: hockey, women, team, family, two 
 Topic 10: hockey, team, olympics, indian, medal 
 Topic 11: world, team, games, athletes, olympics 
 Topic 12: medal, gold, olympics, tokyo, bronze 
 Topic 13: indian, hockey, olympics, tokyo, olympic 
 Topic 14: mirabai, olympic, weightlifting, chanu, tokyo 
 Topic 15: borgohain, boxing, lovlina, medal, will 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 6 (approx. per word bound = -7.032, relative change = 4.539e-04) 
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Completed E-Step (0 seconds). 
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Completing Iteration 7 (approx. per word bound = -7.030, relative change = 2.736e-04) 
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Completed E-Step (0 seconds). 
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Completing Iteration 8 (approx. per word bound = -7.029, relative change = 1.844e-04) 
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Completed E-Step (0 seconds). 
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Completing Iteration 9 (approx. per word bound = -7.028, relative change = 1.421e-04) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 10 (approx. per word bound = -7.027, relative change = 1.065e-04) 
Topic 1: india, hockey, match, olympics, will 
 Topic 2: indian, will, tennis, tokyo, games 
 Topic 3: women's, round, men's, olympics, will 
 Topic 4: team, hockey, women's, indian, india 
 Topic 5: sports, olympics, athletes, tokyo, india 
 Topic 6: team, hockey, india, medal, singh 
 Topic 7: sindhu, olympics, medal, bronze, tokyo 
 Topic 8: aditi, us, olympics, golf, medal 
 Topic 9: hockey, team, women, family, two 
 Topic 10: hockey, team, olympics, indian, medal 
 Topic 11: world, team, games, athletes, olympics 
 Topic 12: medal, gold, olympics, tokyo, bronze 
 Topic 13: indian, hockey, olympics, tokyo, olympic 
 Topic 14: mirabai, olympic, weightlifting, chanu, medal 
 Topic 15: borgohain, boxing, lovlina, medal, will 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 11 (approx. per word bound = -7.026, relative change = 8.467e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 12 (approx. per word bound = -7.026, relative change = 8.000e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 13 (approx. per word bound = -7.025, relative change = 6.415e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 14 (approx. per word bound = -7.025, relative change = 5.470e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 15 (approx. per word bound = -7.025, relative change = 5.860e-05) 
Topic 1: india, hockey, match, olympics, will 
 Topic 2: indian, will, tennis, tokyo, games 
 Topic 3: women's, round, men's, olympics, will 
 Topic 4: team, hockey, women's, indian, india 
 Topic 5: sports, olympics, athletes, tokyo, india 
 Topic 6: team, hockey, medal, india, singh 
 Topic 7: sindhu, olympics, medal, tokyo, bronze 
 Topic 8: aditi, us, olympics, golf, medal 
 Topic 9: hockey, team, women, family, two 
 Topic 10: hockey, team, olympics, indian, medal 
 Topic 11: world, team, games, athletes, olympics 
 Topic 12: medal, gold, olympics, tokyo, bronze 
 Topic 13: indian, hockey, olympics, tokyo, olympic 
 Topic 14: mirabai, olympic, medal, weightlifting, chanu 
 Topic 15: borgohain, lovlina, boxing, medal, will 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 16 (approx. per word bound = -7.024, relative change = 6.905e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 17 (approx. per word bound = -7.024, relative change = 4.568e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 18 (approx. per word bound = -7.024, relative change = 2.546e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 19 (approx. per word bound = -7.024, relative change = 2.488e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 20 (approx. per word bound = -7.023, relative change = 2.173e-05) 
Topic 1: india, hockey, match, olympics, will 
 Topic 2: indian, will, tennis, tokyo, games 
 Topic 3: women's, round, men's, olympics, will 
 Topic 4: team, hockey, women's, indian, india 
 Topic 5: sports, olympics, athletes, tokyo, india 
 Topic 6: team, hockey, medal, singh, india 
 Topic 7: sindhu, olympics, medal, tokyo, bronze 
 Topic 8: aditi, us, olympics, golf, medal 
 Topic 9: hockey, team, women, family, two 
 Topic 10: hockey, team, olympics, indian, players 
 Topic 11: world, team, games, athletes, olympics 
 Topic 12: medal, gold, olympics, tokyo, bronze 
 Topic 13: indian, hockey, olympics, tokyo, olympic 
 Topic 14: mirabai, olympic, medal, weightlifting, chanu 
 Topic 15: borgohain, lovlina, boxing, medal, will 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 21 (approx. per word bound = -7.023, relative change = 2.175e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 22 (approx. per word bound = -7.023, relative change = 2.225e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 23 (approx. per word bound = -7.023, relative change = 2.018e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 24 (approx. per word bound = -7.023, relative change = 1.662e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 25 (approx. per word bound = -7.023, relative change = 1.570e-05) 
Topic 1: india, hockey, match, olympics, will 
 Topic 2: indian, will, tennis, tokyo, games 
 Topic 3: women's, round, men's, olympics, will 
 Topic 4: team, hockey, women's, indian, india 
 Topic 5: sports, olympics, athletes, india, tokyo 
 Topic 6: team, hockey, medal, singh, india 
 Topic 7: sindhu, olympics, medal, tokyo, bronze 
 Topic 8: aditi, us, olympics, golf, medal 
 Topic 9: hockey, team, women, family, caste 
 Topic 10: hockey, team, olympics, indian, players 
 Topic 11: world, team, games, athletes, olympics 
 Topic 12: medal, gold, olympics, tokyo, bronze 
 Topic 13: indian, hockey, olympics, tokyo, olympic 
 Topic 14: mirabai, olympic, medal, chanu, weightlifting 
 Topic 15: borgohain, lovlina, boxing, medal, will 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 26 (approx. per word bound = -7.023, relative change = 1.519e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 27 (approx. per word bound = -7.022, relative change = 1.591e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 28 (approx. per word bound = -7.022, relative change = 1.572e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 29 (approx. per word bound = -7.022, relative change = 1.482e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 30 (approx. per word bound = -7.022, relative change = 1.342e-05) 
Topic 1: india, hockey, match, olympics, will 
 Topic 2: indian, will, tennis, tokyo, games 
 Topic 3: women's, round, men's, olympics, will 
 Topic 4: team, hockey, women's, indian, india 
 Topic 5: sports, olympics, athletes, india, tokyo 
 Topic 6: team, hockey, medal, singh, india 
 Topic 7: sindhu, olympics, medal, tokyo, bronze 
 Topic 8: aditi, us, olympics, golf, medal 
 Topic 9: hockey, team, women, family, caste 
 Topic 10: hockey, team, olympics, indian, players 
 Topic 11: world, team, games, athletes, olympics 
 Topic 12: medal, gold, olympics, tokyo, bronze 
 Topic 13: indian, hockey, olympics, tokyo, olympic 
 Topic 14: mirabai, olympic, medal, chanu, weightlifting 
 Topic 15: borgohain, lovlina, boxing, medal, will 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 31 (approx. per word bound = -7.022, relative change = 1.264e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 32 (approx. per word bound = -7.022, relative change = 1.551e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 33 (approx. per word bound = -7.022, relative change = 1.542e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 34 (approx. per word bound = -7.022, relative change = 1.252e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 35 (approx. per word bound = -7.022, relative change = 1.059e-05) 
Topic 1: india, hockey, match, olympics, will 
 Topic 2: indian, will, tennis, tokyo, games 
 Topic 3: women's, round, men's, olympics, will 
 Topic 4: team, hockey, women's, indian, india 
 Topic 5: sports, olympics, athletes, india, tokyo 
 Topic 6: team, hockey, medal, singh, india 
 Topic 7: sindhu, olympics, medal, tokyo, bronze 
 Topic 8: aditi, us, olympics, golf, medal 
 Topic 9: hockey, team, women, family, caste 
 Topic 10: hockey, team, olympics, indian, players 
 Topic 11: world, team, games, athletes, olympics 
 Topic 12: medal, gold, olympics, tokyo, bronze 
 Topic 13: indian, hockey, olympics, tokyo, olympic 
 Topic 14: mirabai, olympic, medal, chanu, weightlifting 
 Topic 15: borgohain, lovlina, boxing, medal, will 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Model Converged 
Beginning Spectral Initialization 
     Calculating the gram matrix...
     Using only 10000 most frequent terms during initialization...
     Finding anchor words...
    .........................
     Recovering initialization...
    ....................................................................................................
Initialization complete.
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 1 (approx. per word bound = -7.735) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 2 (approx. per word bound = -6.913, relative change = 1.062e-01) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 3 (approx. per word bound = -6.818, relative change = 1.375e-02) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 4 (approx. per word bound = -6.799, relative change = 2.774e-03) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 5 (approx. per word bound = -6.791, relative change = 1.290e-03) 
Topic 1: india, hockey, match, olympics, tokyo 
 Topic 2: olympics, indian, tokyo, will, india 
 Topic 3: women's, men's, ist, will, round 
 Topic 4: award, hockey, dhyan, chand, ratna 
 Topic 5: sports, athletes, olympics, mirabai, india 
 Topic 6: singh, india, hockey, medal, team 
 Topic 7: sindhu, olympics, medal, pv, bronze 
 Topic 8: aditi, golf, olympics, medal, ashok 
 Topic 9: hockey, family, team, caste, women 
 Topic 10: hockey, team, sports, indian, players 
 Topic 11: athletes, biles, world, games, osaka 
 Topic 12: gold, medal, olympics, tokyo, india 
 Topic 13: hockey, indian, medal, sport, women 
 Topic 14: mirabai, olympic, chanu, video, hain 
 Topic 15: borgohain, lovlina, boxing, will, olympic 
 Topic 16: hockey, father, medal, team, singh 
 Topic 17: india, team, penalty, first, indian 
 Topic 18: olympics, medal, olympic, mary, tokyo 
 Topic 19: team, hockey, indian, india, women's 
 Topic 20: team, das, jadhav, two, round 
 Topic 21: sindhu, world, indian, game, games 
 Topic 22: women, olympics, sports, games, tokyo 
 Topic 23: medal, bronze, match, hockey, india 
 Topic 24: sharath, match, us, long, win 
 Topic 25: women's, games, quinn, participating, will 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 6 (approx. per word bound = -6.785, relative change = 7.619e-04) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 7 (approx. per word bound = -6.782, relative change = 5.460e-04) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 8 (approx. per word bound = -6.779, relative change = 3.898e-04) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 9 (approx. per word bound = -6.777, relative change = 2.941e-04) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 10 (approx. per word bound = -6.775, relative change = 2.315e-04) 
Topic 1: india, hockey, match, olympics, tokyo 
 Topic 2: olympics, indian, tokyo, will, india 
 Topic 3: women's, men's, ist, will, round 
 Topic 4: award, hockey, dhyan, chand, ratna 
 Topic 5: sports, athletes, olympics, mirabai, medal 
 Topic 6: singh, india, hockey, medal, team 
 Topic 7: sindhu, olympics, pv, medal, tokyo 
 Topic 8: aditi, golf, olympics, medal, ashok 
 Topic 9: hockey, family, team, women, caste 
 Topic 10: hockey, sports, team, indian, players 
 Topic 11: athletes, biles, world, games, osaka 
 Topic 12: gold, medal, olympics, tokyo, india 
 Topic 13: medal, indian, hockey, women, tokyo 
 Topic 14: mirabai, olympic, chanu, video, hain 
 Topic 15: borgohain, lovlina, boxing, will, olympic 
 Topic 16: hockey, father, medal, team, singh 
 Topic 17: india, team, penalty, first, indian 
 Topic 18: olympics, medal, olympic, mary, tokyo 
 Topic 19: team, hockey, indian, india, women's 
 Topic 20: team, das, jadhav, two, round 
 Topic 21: sindhu, world, indian, game, games 
 Topic 22: women, olympics, sports, tokyo, olympic 
 Topic 23: medal, bronze, match, hockey, india 
 Topic 24: sharath, match, us, win, long 
 Topic 25: women's, games, olympic, quinn, olympics 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 11 (approx. per word bound = -6.775, relative change = 1.320e-04) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 12 (approx. per word bound = -6.774, relative change = 8.597e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 13 (approx. per word bound = -6.773, relative change = 7.917e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 14 (approx. per word bound = -6.773, relative change = 8.484e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 15 (approx. per word bound = -6.772, relative change = 7.312e-05) 
Topic 1: india, hockey, match, olympics, tokyo 
 Topic 2: olympics, indian, tokyo, will, india 
 Topic 3: women's, men's, ist, will, india 
 Topic 4: award, hockey, dhyan, chand, ratna 
 Topic 5: sports, athletes, olympics, mirabai, medal 
 Topic 6: singh, hockey, india, medal, team 
 Topic 7: sindhu, olympics, pv, medal, tokyo 
 Topic 8: aditi, golf, olympics, medal, ashok 
 Topic 9: hockey, family, team, women, caste 
 Topic 10: hockey, sports, team, indian, players 
 Topic 11: athletes, world, biles, games, osaka 
 Topic 12: gold, medal, olympics, tokyo, india 
 Topic 13: medal, indian, women, hockey, tokyo 
 Topic 14: mirabai, olympic, chanu, video, hain 
 Topic 15: borgohain, lovlina, boxing, will, olympic 
 Topic 16: hockey, father, medal, singh, team 
 Topic 17: india, team, penalty, first, indian 
 Topic 18: olympics, medal, olympic, mary, tokyo 
 Topic 19: team, hockey, indian, india, women's 
 Topic 20: team, das, jadhav, two, round 
 Topic 21: sindhu, world, game, indian, games 
 Topic 22: women, olympics, sports, olympic, tokyo 
 Topic 23: medal, bronze, match, hockey, india 
 Topic 24: sharath, match, us, long, win 
 Topic 25: women's, gurjit, games, kaur, hockey 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 16 (approx. per word bound = -6.772, relative change = 6.206e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 17 (approx. per word bound = -6.772, relative change = 5.374e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 18 (approx. per word bound = -6.771, relative change = 3.822e-05) 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 19 (approx. per word bound = -6.771, relative change = 2.177e-05) 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 20 (approx. per word bound = -6.771, relative change = 1.861e-05) 
Topic 1: india, hockey, match, olympics, tokyo 
 Topic 2: olympics, indian, tokyo, will, india 
 Topic 3: women's, men's, ist, will, india 
 Topic 4: award, hockey, dhyan, chand, ratna 
 Topic 5: sports, athletes, olympics, mirabai, medal 
 Topic 6: singh, hockey, india, medal, team 
 Topic 7: sindhu, olympics, pv, medal, tokyo 
 Topic 8: aditi, golf, olympics, medal, ashok 
 Topic 9: hockey, family, team, caste, women 
 Topic 10: hockey, sports, team, indian, players 
 Topic 11: athletes, world, biles, games, osaka 
 Topic 12: gold, medal, olympics, tokyo, india 
 Topic 13: medal, indian, women, tokyo, hockey 
 Topic 14: mirabai, olympic, chanu, video, hain 
 Topic 15: borgohain, lovlina, boxing, will, olympic 
 Topic 16: hockey, father, medal, singh, team 
 Topic 17: india, team, penalty, first, indian 
 Topic 18: olympics, medal, olympic, mary, tokyo 
 Topic 19: team, hockey, indian, india, women's 
 Topic 20: team, das, jadhav, two, round 
 Topic 21: sindhu, world, game, indian, games 
 Topic 22: women, olympics, sports, olympic, tokyo 
 Topic 23: medal, bronze, match, hockey, india 
 Topic 24: sharath, match, us, long, win 
 Topic 25: women's, gurjit, kaur, games, fourth 
.....................................................................................................................
Completed E-Step (0 seconds). 
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Completing Iteration 21 (approx. per word bound = -6.771, relative change = 1.990e-05) 
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Completing Iteration 22 (approx. per word bound = -6.771, relative change = 1.027e-05) 
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Completing Iteration 23 (approx. per word bound = -6.771, relative change = 2.970e-05) 
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Completing Iteration 24 (approx. per word bound = -6.770, relative change = 4.427e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 25 (approx. per word bound = -6.770, relative change = 3.369e-05) 
Topic 1: india, hockey, match, olympics, tokyo 
 Topic 2: olympics, indian, tokyo, will, india 
 Topic 3: women's, men's, ist, will, india 
 Topic 4: award, dhyan, hockey, chand, ratna 
 Topic 5: sports, athletes, olympics, mirabai, medal 
 Topic 6: singh, hockey, india, medal, team 
 Topic 7: sindhu, olympics, pv, medal, tokyo 
 Topic 8: aditi, golf, olympics, medal, ashok 
 Topic 9: hockey, family, team, caste, women 
 Topic 10: hockey, sports, team, indian, players 
 Topic 11: athletes, world, biles, games, osaka 
 Topic 12: gold, medal, olympics, tokyo, india 
 Topic 13: medal, indian, women, tokyo, hockey 
 Topic 14: mirabai, olympic, chanu, video, hain 
 Topic 15: borgohain, lovlina, boxing, will, olympic 
 Topic 16: hockey, father, medal, singh, team 
 Topic 17: india, team, penalty, first, indian 
 Topic 18: olympics, medal, olympic, mary, tokyo 
 Topic 19: team, hockey, indian, india, medal 
 Topic 20: team, das, jadhav, two, round 
 Topic 21: sindhu, world, game, indian, games 
 Topic 22: women, olympics, sports, olympic, tokyo 
 Topic 23: medal, match, bronze, india, hockey 
 Topic 24: sharath, match, us, long, win 
 Topic 25: women's, hockey, kaur, women, first 
.....................................................................................................................
Completed E-Step (0 seconds). 
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Completing Iteration 26 (approx. per word bound = -6.770, relative change = 3.935e-05) 
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Completing Iteration 27 (approx. per word bound = -6.770, relative change = 3.239e-05) 
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Completing Iteration 28 (approx. per word bound = -6.769, relative change = 2.925e-05) 
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Completing Iteration 29 (approx. per word bound = -6.769, relative change = 2.249e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 30 (approx. per word bound = -6.769, relative change = 2.248e-05) 
Topic 1: india, hockey, match, olympics, tokyo 
 Topic 2: olympics, indian, tokyo, will, india 
 Topic 3: women's, men's, ist, will, india 
 Topic 4: award, dhyan, chand, hockey, ratna 
 Topic 5: sports, athletes, olympics, mirabai, medal 
 Topic 6: singh, hockey, india, team, medal 
 Topic 7: sindhu, olympics, pv, medal, tokyo 
 Topic 8: aditi, golf, olympics, medal, ashok 
 Topic 9: hockey, family, team, caste, women 
 Topic 10: hockey, sports, team, indian, players 
 Topic 11: athletes, world, biles, games, osaka 
 Topic 12: gold, medal, olympics, tokyo, india 
 Topic 13: medal, indian, women, tokyo, olympic 
 Topic 14: mirabai, olympic, chanu, video, hain 
 Topic 15: borgohain, lovlina, boxing, will, olympic 
 Topic 16: hockey, father, medal, singh, team 
 Topic 17: india, team, penalty, first, indian 
 Topic 18: olympics, medal, olympic, mary, tokyo 
 Topic 19: team, hockey, indian, india, medal 
 Topic 20: team, das, jadhav, two, round 
 Topic 21: sindhu, world, game, indian, games 
 Topic 22: women, olympics, sports, olympic, tokyo 
 Topic 23: medal, match, bronze, india, hockey 
 Topic 24: sharath, match, us, long, win 
 Topic 25: women's, hockey, women, first, olympics 
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Completed E-Step (0 seconds). 
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Completing Iteration 31 (approx. per word bound = -6.769, relative change = 1.948e-05) 
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Completing Iteration 32 (approx. per word bound = -6.769, relative change = 2.308e-05) 
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Completing Iteration 33 (approx. per word bound = -6.769, relative change = 2.112e-05) 
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Completing Iteration 34 (approx. per word bound = -6.769, relative change = 1.914e-05) 
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Completing Iteration 35 (approx. per word bound = -6.768, relative change = 2.410e-05) 
Topic 1: india, hockey, match, olympics, tokyo 
 Topic 2: olympics, indian, tokyo, will, india 
 Topic 3: women's, men's, ist, will, india 
 Topic 4: award, dhyan, chand, ratna, hockey 
 Topic 5: sports, athletes, olympics, mirabai, medal 
 Topic 6: singh, hockey, india, team, medal 
 Topic 7: sindhu, olympics, pv, medal, tokyo 
 Topic 8: aditi, golf, olympics, medal, ashok 
 Topic 9: hockey, family, team, caste, women 
 Topic 10: hockey, sports, team, indian, players 
 Topic 11: athletes, world, biles, games, osaka 
 Topic 12: gold, medal, olympics, tokyo, india 
 Topic 13: medal, indian, women, tokyo, olympic 
 Topic 14: mirabai, olympic, chanu, video, hain 
 Topic 15: borgohain, lovlina, boxing, will, olympic 
 Topic 16: hockey, father, medal, singh, team 
 Topic 17: india, team, penalty, first, indian 
 Topic 18: olympics, medal, olympic, mary, tokyo 
 Topic 19: team, hockey, indian, india, medal 
 Topic 20: team, das, jadhav, two, round 
 Topic 21: sindhu, world, game, indian, games 
 Topic 22: women, olympics, sports, olympic, tokyo 
 Topic 23: medal, match, bronze, india, hockey 
 Topic 24: sharath, match, us, long, win 
 Topic 25: women's, hockey, team, women, olympics 
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Completed E-Step (0 seconds). 
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Completing Iteration 36 (approx. per word bound = -6.768, relative change = 2.531e-05) 
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Completing Iteration 37 (approx. per word bound = -6.768, relative change = 2.450e-05) 
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Completing Iteration 38 (approx. per word bound = -6.768, relative change = 2.447e-05) 
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Completing Iteration 39 (approx. per word bound = -6.768, relative change = 2.512e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 40 (approx. per word bound = -6.768, relative change = 2.534e-05) 
Topic 1: india, hockey, match, olympics, tokyo 
 Topic 2: olympics, indian, tokyo, will, india 
 Topic 3: women's, men's, ist, will, india 
 Topic 4: award, dhyan, chand, ratna, hockey 
 Topic 5: sports, athletes, olympics, mirabai, medal 
 Topic 6: singh, hockey, india, team, medal 
 Topic 7: sindhu, olympics, pv, medal, tokyo 
 Topic 8: aditi, golf, olympics, medal, ashok 
 Topic 9: hockey, family, team, caste, women 
 Topic 10: hockey, sports, team, indian, players 
 Topic 11: athletes, world, biles, games, osaka 
 Topic 12: gold, medal, olympics, tokyo, india 
 Topic 13: medal, indian, women, tokyo, olympic 
 Topic 14: mirabai, olympic, chanu, video, hain 
 Topic 15: borgohain, lovlina, boxing, will, olympic 
 Topic 16: hockey, father, medal, singh, team 
 Topic 17: india, team, penalty, first, two 
 Topic 18: olympics, medal, olympic, mary, tokyo 
 Topic 19: team, hockey, indian, india, medal 
 Topic 20: team, das, jadhav, two, round 
 Topic 21: sindhu, world, game, indian, games 
 Topic 22: women, olympics, sports, olympic, tokyo 
 Topic 23: medal, match, bronze, india, hockey 
 Topic 24: sharath, match, us, long, win 
 Topic 25: women's, hockey, team, women, olympics 
.....................................................................................................................
Completed E-Step (0 seconds). 
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Completing Iteration 41 (approx. per word bound = -6.767, relative change = 2.624e-05) 
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Completing Iteration 42 (approx. per word bound = -6.767, relative change = 2.570e-05) 
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Completing Iteration 43 (approx. per word bound = -6.767, relative change = 2.005e-05) 
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Completing Iteration 44 (approx. per word bound = -6.767, relative change = 1.707e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 45 (approx. per word bound = -6.767, relative change = 1.771e-05) 
Topic 1: india, hockey, match, olympics, tokyo 
 Topic 2: olympics, indian, tokyo, will, india 
 Topic 3: women's, men's, ist, will, india 
 Topic 4: award, dhyan, chand, ratna, hockey 
 Topic 5: sports, athletes, olympics, mirabai, medal 
 Topic 6: singh, hockey, india, team, medal 
 Topic 7: sindhu, olympics, pv, medal, tokyo 
 Topic 8: aditi, golf, olympics, medal, ashok 
 Topic 9: hockey, family, team, caste, women 
 Topic 10: hockey, sports, team, indian, players 
 Topic 11: athletes, world, biles, games, osaka 
 Topic 12: gold, medal, olympics, tokyo, india 
 Topic 13: medal, indian, women, tokyo, olympic 
 Topic 14: mirabai, olympic, chanu, video, hain 
 Topic 15: borgohain, lovlina, boxing, will, olympic 
 Topic 16: hockey, father, medal, singh, team 
 Topic 17: india, team, penalty, first, two 
 Topic 18: olympics, medal, olympic, mary, tokyo 
 Topic 19: team, hockey, indian, india, medal 
 Topic 20: team, das, jadhav, two, round 
 Topic 21: sindhu, world, game, indian, games 
 Topic 22: women, olympics, sports, olympic, tokyo 
 Topic 23: medal, match, bronze, india, hockey 
 Topic 24: sharath, match, us, long, win 
 Topic 25: women's, hockey, team, women, indian 
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Completed E-Step (0 seconds). 
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Completing Iteration 46 (approx. per word bound = -6.767, relative change = 1.926e-05) 
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Completing Iteration 47 (approx. per word bound = -6.767, relative change = 1.981e-05) 
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Completing Iteration 48 (approx. per word bound = -6.766, relative change = 2.074e-05) 
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Completing Iteration 49 (approx. per word bound = -6.766, relative change = 2.145e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 50 (approx. per word bound = -6.766, relative change = 2.412e-05) 
Topic 1: india, hockey, match, olympics, tokyo 
 Topic 2: olympics, indian, tokyo, will, india 
 Topic 3: women's, men's, ist, will, india 
 Topic 4: award, dhyan, chand, ratna, hockey 
 Topic 5: sports, athletes, olympics, mirabai, medal 
 Topic 6: singh, hockey, india, team, medal 
 Topic 7: sindhu, olympics, pv, medal, tokyo 
 Topic 8: aditi, golf, olympics, medal, ashok 
 Topic 9: hockey, family, team, caste, women 
 Topic 10: hockey, sports, team, indian, players 
 Topic 11: athletes, world, biles, games, osaka 
 Topic 12: gold, medal, olympics, tokyo, india 
 Topic 13: medal, indian, women, tokyo, olympic 
 Topic 14: mirabai, olympic, chanu, video, hain 
 Topic 15: borgohain, lovlina, boxing, will, olympic 
 Topic 16: hockey, father, medal, singh, team 
 Topic 17: india, team, penalty, first, two 
 Topic 18: olympics, medal, olympic, mary, tokyo 
 Topic 19: team, hockey, indian, india, medal 
 Topic 20: team, das, jadhav, two, round 
 Topic 21: sindhu, world, game, indian, games 
 Topic 22: women, olympics, sports, olympic, tokyo 
 Topic 23: medal, match, bronze, india, hockey 
 Topic 24: sharath, match, us, long, win 
 Topic 25: women's, hockey, team, indian, women 
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Completed E-Step (0 seconds). 
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Completing Iteration 51 (approx. per word bound = -6.766, relative change = 2.470e-05) 
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Completing Iteration 52 (approx. per word bound = -6.766, relative change = 2.382e-05) 
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Completing Iteration 53 (approx. per word bound = -6.766, relative change = 2.137e-05) 
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Completing Iteration 54 (approx. per word bound = -6.766, relative change = 2.055e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 55 (approx. per word bound = -6.765, relative change = 2.243e-05) 
Topic 1: india, hockey, match, olympics, tokyo 
 Topic 2: olympics, indian, tokyo, will, india 
 Topic 3: women's, men's, ist, will, india 
 Topic 4: award, dhyan, chand, ratna, hockey 
 Topic 5: sports, athletes, olympics, mirabai, medal 
 Topic 6: singh, hockey, india, team, medal 
 Topic 7: sindhu, olympics, pv, medal, tokyo 
 Topic 8: aditi, golf, olympics, medal, ashok 
 Topic 9: hockey, family, team, caste, women 
 Topic 10: hockey, sports, team, indian, players 
 Topic 11: athletes, world, biles, games, osaka 
 Topic 12: gold, medal, olympics, tokyo, won 
 Topic 13: medal, indian, women, tokyo, olympic 
 Topic 14: mirabai, olympic, chanu, video, hain 
 Topic 15: borgohain, lovlina, boxing, will, olympic 
 Topic 16: hockey, father, medal, singh, team 
 Topic 17: india, team, penalty, first, two 
 Topic 18: olympics, medal, olympic, mary, tokyo 
 Topic 19: team, hockey, indian, india, medal 
 Topic 20: team, das, jadhav, two, round 
 Topic 21: sindhu, world, game, indian, games 
 Topic 22: women, olympics, sports, olympic, tokyo 
 Topic 23: medal, match, bronze, india, hockey 
 Topic 24: sharath, match, us, long, win 
 Topic 25: women's, hockey, team, indian, women 
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Completed E-Step (0 seconds). 
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Completing Iteration 56 (approx. per word bound = -6.765, relative change = 2.104e-05) 
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Completing Iteration 57 (approx. per word bound = -6.765, relative change = 2.226e-05) 
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Completing Iteration 58 (approx. per word bound = -6.765, relative change = 2.166e-05) 
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Completing Iteration 59 (approx. per word bound = -6.765, relative change = 2.200e-05) 
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Completing Iteration 60 (approx. per word bound = -6.765, relative change = 2.379e-05) 
Topic 1: india, hockey, match, olympics, tokyo 
 Topic 2: olympics, indian, tokyo, will, india 
 Topic 3: women's, men's, ist, will, india 
 Topic 4: award, dhyan, chand, ratna, hockey 
 Topic 5: sports, athletes, olympics, mirabai, medal 
 Topic 6: singh, hockey, india, team, medal 
 Topic 7: sindhu, olympics, pv, medal, tokyo 
 Topic 8: aditi, golf, olympics, medal, ashok 
 Topic 9: hockey, family, team, caste, women 
 Topic 10: hockey, sports, team, indian, players 
 Topic 11: athletes, world, biles, games, osaka 
 Topic 12: gold, medal, olympics, tokyo, won 
 Topic 13: medal, indian, women, tokyo, olympic 
 Topic 14: mirabai, olympic, chanu, video, hain 
 Topic 15: borgohain, lovlina, boxing, will, olympic 
 Topic 16: hockey, father, medal, singh, team 
 Topic 17: india, team, penalty, first, two 
 Topic 18: olympics, medal, olympic, mary, tokyo 
 Topic 19: team, hockey, indian, india, medal 
 Topic 20: team, das, jadhav, two, round 
 Topic 21: sindhu, world, game, indian, games 
 Topic 22: women, olympics, sports, olympic, tokyo 
 Topic 23: medal, match, bronze, india, hockey 
 Topic 24: sharath, match, us, long, win 
 Topic 25: women's, hockey, team, indian, women 
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Completed E-Step (0 seconds). 
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Completing Iteration 61 (approx. per word bound = -6.764, relative change = 2.313e-05) 
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Completing Iteration 62 (approx. per word bound = -6.764, relative change = 2.005e-05) 
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Completing Iteration 63 (approx. per word bound = -6.764, relative change = 1.923e-05) 
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Completing Iteration 64 (approx. per word bound = -6.764, relative change = 1.961e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 65 (approx. per word bound = -6.764, relative change = 2.010e-05) 
Topic 1: india, hockey, match, olympics, tokyo 
 Topic 2: olympics, indian, tokyo, will, india 
 Topic 3: women's, men's, ist, will, india 
 Topic 4: award, dhyan, chand, ratna, hockey 
 Topic 5: sports, athletes, olympics, mirabai, medal 
 Topic 6: singh, hockey, india, team, medal 
 Topic 7: sindhu, olympics, pv, medal, tokyo 
 Topic 8: aditi, golf, olympics, medal, ashok 
 Topic 9: hockey, family, team, caste, women 
 Topic 10: hockey, sports, team, indian, players 
 Topic 11: athletes, world, biles, games, osaka 
 Topic 12: gold, medal, olympics, tokyo, won 
 Topic 13: medal, indian, women, tokyo, olympic 
 Topic 14: mirabai, olympic, chanu, video, hain 
 Topic 15: borgohain, lovlina, boxing, will, olympic 
 Topic 16: hockey, father, medal, singh, team 
 Topic 17: india, team, penalty, first, two 
 Topic 18: olympics, medal, olympic, mary, tokyo 
 Topic 19: team, hockey, indian, india, medal 
 Topic 20: team, das, jadhav, two, round 
 Topic 21: sindhu, world, game, indian, games 
 Topic 22: women, olympics, sports, olympic, tokyo 
 Topic 23: medal, bronze, match, india, hockey 
 Topic 24: sharath, match, us, long, win 
 Topic 25: women's, hockey, team, indian, women 
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Completed E-Step (0 seconds). 
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Completing Iteration 66 (approx. per word bound = -6.764, relative change = 2.036e-05) 
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Completing Iteration 67 (approx. per word bound = -6.764, relative change = 2.001e-05) 
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Completing Iteration 68 (approx. per word bound = -6.764, relative change = 1.824e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 69 (approx. per word bound = -6.763, relative change = 1.772e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 70 (approx. per word bound = -6.763, relative change = 1.694e-05) 
Topic 1: india, hockey, match, olympics, tokyo 
 Topic 2: olympics, indian, tokyo, will, india 
 Topic 3: women's, men's, ist, will, india 
 Topic 4: award, dhyan, chand, ratna, hockey 
 Topic 5: sports, athletes, olympics, mirabai, medal 
 Topic 6: singh, hockey, india, team, medal 
 Topic 7: sindhu, olympics, pv, medal, tokyo 
 Topic 8: aditi, golf, olympics, medal, ashok 
 Topic 9: hockey, family, team, caste, women 
 Topic 10: hockey, sports, team, indian, players 
 Topic 11: athletes, world, biles, games, osaka 
 Topic 12: gold, medal, olympics, tokyo, won 
 Topic 13: medal, indian, women, tokyo, olympic 
 Topic 14: mirabai, olympic, chanu, video, hain 
 Topic 15: borgohain, lovlina, boxing, will, olympic 
 Topic 16: hockey, father, medal, singh, team 
 Topic 17: india, team, penalty, first, two 
 Topic 18: olympics, medal, olympic, mary, tokyo 
 Topic 19: team, hockey, indian, india, medal 
 Topic 20: team, das, jadhav, two, round 
 Topic 21: sindhu, world, game, indian, games 
 Topic 22: women, olympics, sports, olympic, tokyo 
 Topic 23: medal, bronze, match, india, hockey 
 Topic 24: sharath, match, us, long, win 
 Topic 25: women's, hockey, team, indian, women 
.....................................................................................................................
Completed E-Step (0 seconds). 
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Completing Iteration 71 (approx. per word bound = -6.763, relative change = 1.657e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 72 (approx. per word bound = -6.763, relative change = 1.534e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 73 (approx. per word bound = -6.763, relative change = 1.407e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 74 (approx. per word bound = -6.763, relative change = 1.225e-05) 
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Completed E-Step (0 seconds). 
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Completing Iteration 75 (approx. per word bound = -6.763, relative change = 1.225e-05) 
Topic 1: india, hockey, match, olympics, tokyo 
 Topic 2: olympics, indian, tokyo, will, india 
 Topic 3: women's, men's, ist, will, india 
 Topic 4: award, dhyan, chand, ratna, hockey 
 Topic 5: sports, athletes, olympics, mirabai, medal 
 Topic 6: singh, hockey, india, team, medal 
 Topic 7: sindhu, olympics, pv, medal, tokyo 
 Topic 8: aditi, golf, olympics, medal, ashok 
 Topic 9: hockey, family, team, caste, women 
 Topic 10: hockey, sports, team, indian, players 
 Topic 11: athletes, world, biles, games, osaka 
 Topic 12: gold, medal, olympics, tokyo, won 
 Topic 13: medal, indian, women, tokyo, olympic 
 Topic 14: mirabai, olympic, chanu, video, hain 
 Topic 15: borgohain, lovlina, boxing, will, olympic 
 Topic 16: hockey, father, medal, singh, team 
 Topic 17: india, team, penalty, first, two 
 Topic 18: olympics, medal, olympic, mary, tokyo 
 Topic 19: team, hockey, indian, india, medal 
 Topic 20: team, das, jadhav, two, round 
 Topic 21: sindhu, world, game, indian, games 
 Topic 22: women, olympics, sports, olympic, tokyo 
 Topic 23: medal, bronze, match, india, hockey 
 Topic 24: sharath, match, us, long, win 
 Topic 25: women's, hockey, team, indian, olympics 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 76 (approx. per word bound = -6.763, relative change = 1.283e-05) 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 77 (approx. per word bound = -6.763, relative change = 1.285e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 78 (approx. per word bound = -6.763, relative change = 1.334e-05) 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 79 (approx. per word bound = -6.762, relative change = 1.413e-05) 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 80 (approx. per word bound = -6.762, relative change = 1.490e-05) 
Topic 1: india, hockey, match, olympics, tokyo 
 Topic 2: olympics, indian, tokyo, will, india 
 Topic 3: women's, men's, ist, will, india 
 Topic 4: award, dhyan, chand, ratna, hockey 
 Topic 5: sports, athletes, olympics, mirabai, medal 
 Topic 6: singh, hockey, india, team, medal 
 Topic 7: sindhu, olympics, pv, medal, tokyo 
 Topic 8: aditi, golf, olympics, medal, ashok 
 Topic 9: hockey, family, team, caste, women 
 Topic 10: hockey, sports, team, indian, players 
 Topic 11: athletes, world, biles, games, osaka 
 Topic 12: gold, medal, olympics, tokyo, won 
 Topic 13: medal, indian, tokyo, women, olympic 
 Topic 14: mirabai, olympic, chanu, video, hain 
 Topic 15: borgohain, lovlina, boxing, will, olympic 
 Topic 16: hockey, father, medal, singh, team 
 Topic 17: india, team, penalty, first, two 
 Topic 18: olympics, medal, olympic, mary, tokyo 
 Topic 19: team, hockey, indian, india, medal 
 Topic 20: team, das, jadhav, two, round 
 Topic 21: sindhu, world, game, indian, games 
 Topic 22: women, olympics, sports, olympic, tokyo 
 Topic 23: medal, bronze, match, india, hockey 
 Topic 24: sharath, match, us, long, win 
 Topic 25: women's, hockey, team, indian, olympics 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 81 (approx. per word bound = -6.762, relative change = 1.254e-05) 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 82 (approx. per word bound = -6.762, relative change = 1.220e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 83 (approx. per word bound = -6.762, relative change = 1.253e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 84 (approx. per word bound = -6.762, relative change = 1.247e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 85 (approx. per word bound = -6.762, relative change = 1.198e-05) 
Topic 1: india, hockey, match, olympics, tokyo 
 Topic 2: olympics, indian, tokyo, will, india 
 Topic 3: women's, men's, ist, will, india 
 Topic 4: award, dhyan, chand, ratna, hockey 
 Topic 5: sports, athletes, olympics, mirabai, medal 
 Topic 6: singh, hockey, india, team, medal 
 Topic 7: sindhu, olympics, pv, medal, tokyo 
 Topic 8: aditi, golf, olympics, medal, ashok 
 Topic 9: hockey, family, team, caste, women 
 Topic 10: hockey, sports, team, indian, players 
 Topic 11: athletes, world, biles, games, osaka 
 Topic 12: gold, medal, olympics, tokyo, won 
 Topic 13: medal, indian, tokyo, women, olympic 
 Topic 14: mirabai, olympic, chanu, video, hain 
 Topic 15: borgohain, lovlina, boxing, will, olympic 
 Topic 16: hockey, father, medal, singh, team 
 Topic 17: india, team, penalty, first, two 
 Topic 18: olympics, medal, olympic, mary, tokyo 
 Topic 19: team, hockey, indian, india, medal 
 Topic 20: team, das, jadhav, two, round 
 Topic 21: sindhu, world, game, indian, games 
 Topic 22: women, olympics, sports, olympic, tokyo 
 Topic 23: medal, bronze, match, india, hockey 
 Topic 24: sharath, match, us, long, win 
 Topic 25: women's, hockey, team, indian, olympics 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 86 (approx. per word bound = -6.762, relative change = 1.194e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 87 (approx. per word bound = -6.762, relative change = 1.494e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 88 (approx. per word bound = -6.762, relative change = 1.501e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 89 (approx. per word bound = -6.762, relative change = 1.531e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 90 (approx. per word bound = -6.761, relative change = 1.947e-05) 
Topic 1: india, hockey, match, olympics, tokyo 
 Topic 2: olympics, indian, tokyo, will, india 
 Topic 3: women's, men's, ist, will, india 
 Topic 4: award, dhyan, chand, ratna, hockey 
 Topic 5: sports, athletes, olympics, mirabai, medal 
 Topic 6: singh, hockey, india, team, medal 
 Topic 7: sindhu, olympics, pv, medal, tokyo 
 Topic 8: aditi, golf, olympics, medal, ashok 
 Topic 9: hockey, family, team, caste, women 
 Topic 10: hockey, sports, team, indian, players 
 Topic 11: athletes, world, biles, games, osaka 
 Topic 12: gold, medal, olympics, tokyo, won 
 Topic 13: medal, indian, tokyo, women, olympic 
 Topic 14: mirabai, olympic, chanu, video, hain 
 Topic 15: borgohain, lovlina, boxing, will, olympic 
 Topic 16: hockey, father, medal, singh, team 
 Topic 17: india, team, penalty, first, two 
 Topic 18: olympics, medal, olympic, mary, tokyo 
 Topic 19: team, hockey, indian, india, medal 
 Topic 20: team, das, jadhav, two, round 
 Topic 21: sindhu, world, game, indian, games 
 Topic 22: women, olympics, sports, olympic, tokyo 
 Topic 23: medal, bronze, match, india, hockey 
 Topic 24: sharath, match, us, long, win 
 Topic 25: women's, hockey, team, indian, olympics 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 91 (approx. per word bound = -6.761, relative change = 1.806e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 92 (approx. per word bound = -6.761, relative change = 1.489e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 93 (approx. per word bound = -6.761, relative change = 1.177e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 94 (approx. per word bound = -6.761, relative change = 1.014e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 95 (approx. per word bound = -6.761, relative change = 1.011e-05) 
Topic 1: india, hockey, match, olympics, tokyo 
 Topic 2: olympics, indian, tokyo, will, india 
 Topic 3: women's, men's, ist, will, india 
 Topic 4: award, dhyan, chand, ratna, hockey 
 Topic 5: sports, athletes, olympics, mirabai, medal 
 Topic 6: singh, hockey, india, team, medal 
 Topic 7: sindhu, olympics, pv, medal, tokyo 
 Topic 8: aditi, golf, olympics, medal, ashok 
 Topic 9: hockey, family, team, caste, women 
 Topic 10: hockey, sports, team, indian, players 
 Topic 11: athletes, world, biles, games, osaka 
 Topic 12: gold, medal, olympics, tokyo, won 
 Topic 13: medal, indian, tokyo, women, olympic 
 Topic 14: mirabai, olympic, chanu, video, hain 
 Topic 15: borgohain, lovlina, boxing, will, olympic 
 Topic 16: hockey, father, medal, singh, team 
 Topic 17: india, team, penalty, first, two 
 Topic 18: olympics, medal, olympic, mary, tokyo 
 Topic 19: team, hockey, indian, india, medal 
 Topic 20: team, das, jadhav, two, round 
 Topic 21: sindhu, world, game, indian, games 
 Topic 22: women, olympics, sports, olympic, tokyo 
 Topic 23: medal, bronze, match, india, hockey 
 Topic 24: sharath, match, us, long, win 
 Topic 25: women's, hockey, team, indian, olympics 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Model Converged 
Beginning Spectral Initialization 
     Calculating the gram matrix...
     Using only 10000 most frequent terms during initialization...
     Finding anchor words...
    ..................................................
     Recovering initialization...
    ....................................................................................................
Initialization complete.
.....................................................................................................................
Completed E-Step (1 seconds). 
Completed M-Step. 
Completing Iteration 1 (approx. per word bound = -7.489) 
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Completed E-Step (1 seconds). 
Completed M-Step. 
Completing Iteration 2 (approx. per word bound = -6.619, relative change = 1.162e-01) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 3 (approx. per word bound = -6.471, relative change = 2.232e-02) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 4 (approx. per word bound = -6.432, relative change = 6.034e-03) 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 5 (approx. per word bound = -6.416, relative change = 2.475e-03) 
Topic 1: india, hockey, olympics, match, tokyo 
 Topic 2: manika, will, olympics, back, athletes 
 Topic 3: women's, ist, will, men's, day 
 Topic 4: lakh, athletes, rs, will, village 
 Topic 5: sports, hockey, city, india, like 
 Topic 6: medal, hockey, bronze, indian, singh 
 Topic 7: sindhu, pv, olympics, tokyo, 2020 
 Topic 8: us, sports, olympics, medal, performance 
 Topic 9: hockey, women, girls, team, even 
 Topic 10: hockey, team, indian, pradesh, academy 
 Topic 11: osaka, open, tokyo, world, last 
 Topic 12: gold, medal, olympics, won, india 
 Topic 13: hockey, indian, sport, olympic, medal 
 Topic 14: mirabai, samantha, video, sunday, akkineni 
 Topic 15: road, minister, state, will, chief 
 Topic 16: hockey, father, medal, singh, family 
 Topic 17: team, india, hockey, women's, indian 
 Topic 18: olympics, age, years, bronze, medal 
 Topic 19: team, hockey, indian, women's, medal 
 Topic 20: pooja, sonam, ichrak, round, winner 
 Topic 21: sindhu, yamaguchi, badminton, first, win 
 Topic 22: games, olympics, women, tokyo, medal 
 Topic 23: medal, hockey, bronze, match, will 
 Topic 24: long, sharath, mary, world, games 
 Topic 25: sports, olympics, women, athletes, will 
 Topic 26: award, dhyan, ratna, chand, khel 
 Topic 27: india, argentina, australia, hockey, team 
 Topic 28: borgohain, lovlina, boxing, boxer, medal 
 Topic 29: medal, gold, chanu, mirabai, tokyo 
 Topic 30: coach, team, india, tokyo, players 
 Topic 31: indian, singh, tokyo, olympics, india 
 Topic 32: das, team, jadhav, set, 10s 
 Topic 33: video, shared, olympics, brand, olympic 
 Topic 34: rs, olympics, hockey, singh, minister 
 Topic 35: aditi, golf, medal, olympics, ashok 
 Topic 36: india, penalty, first, minutes, quarter 
 Topic 37: men's, team, match, indian, air 
 Topic 38: hockey, family, caste, team, village 
 Topic 39: sindhu, won, medal, world, game 
 Topic 40: modi, pm, minister, country, india 
 Topic 41: team, hockey, khan, india, women's 
 Topic 42: singh, india, penalty, goal, team 
 Topic 43: athletes, olympics, games, tokyo, olympic 
 Topic 44: team, players, nba, game, basketball 
 Topic 45: mirabai, medal, olympic, chanu, weightlifting 
 Topic 46: biles, mental, athletes, world, health 
 Topic 47: medal, bronze, gold, punia, tokyo 
 Topic 48: hockey, team, olympics, women's, match 
 Topic 49: india, pool, indian, will, team 
 Topic 50: olympics, indian, best, women's, many 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 6 (approx. per word bound = -6.407, relative change = 1.416e-03) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 7 (approx. per word bound = -6.402, relative change = 8.106e-04) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 8 (approx. per word bound = -6.399, relative change = 4.771e-04) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 9 (approx. per word bound = -6.397, relative change = 3.221e-04) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 10 (approx. per word bound = -6.395, relative change = 2.715e-04) 
Topic 1: india, hockey, olympics, tokyo, match 
 Topic 2: manika, olympics, will, back, athletes 
 Topic 3: women's, ist, will, men's, day 
 Topic 4: athletes, lakh, rs, will, village 
 Topic 5: sports, hockey, city, india, like 
 Topic 6: hockey, medal, team, bronze, indian 
 Topic 7: sindhu, pv, olympics, tokyo, 2020 
 Topic 8: sports, us, olympics, medal, performance 
 Topic 9: hockey, women, girls, team, even 
 Topic 10: hockey, team, indian, pradesh, academy 
 Topic 11: osaka, open, tokyo, world, last 
 Topic 12: gold, medal, olympics, india, won 
 Topic 13: hockey, indian, olympic, sport, medal 
 Topic 14: mirabai, samantha, win, video, sunday 
 Topic 15: road, will, medal, bjp, chief 
 Topic 16: hockey, medal, father, singh, team 
 Topic 17: team, india, hockey, women's, olympics 
 Topic 18: olympics, age, years, bronze, medal 
 Topic 19: team, hockey, indian, women's, match 
 Topic 20: pooja, sonam, ichrak, winner, round 
 Topic 21: sindhu, yamaguchi, win, badminton, first 
 Topic 22: games, olympics, women, tokyo, medal 
 Topic 23: hockey, medal, bronze, india, match 
 Topic 24: sharath, long, mary, world, games 
 Topic 25: sports, olympics, women, athletes, will 
 Topic 26: award, dhyan, ratna, chand, khel 
 Topic 27: india, argentina, australia, hockey, team 
 Topic 28: borgohain, lovlina, boxing, medal, boxer 
 Topic 29: gold, medal, chanu, mirabai, tokyo 
 Topic 30: coach, team, india, medal, tokyo 
 Topic 31: indian, singh, tokyo, olympics, india 
 Topic 32: das, team, jadhav, set, 10s 
 Topic 33: video, shared, olympics, brand, sindhu 
 Topic 34: rs, hockey, olympics, singh, minister 
 Topic 35: aditi, golf, medal, olympics, ashok 
 Topic 36: india, penalty, first, minutes, quarter 
 Topic 37: match, men's, team, indian, air 
 Topic 38: hockey, family, caste, team, village 
 Topic 39: sindhu, won, medal, game, world 
 Topic 40: modi, pm, minister, country, india 
 Topic 41: team, hockey, khan, india, women's 
 Topic 42: india, singh, penalty, goal, team 
 Topic 43: athletes, olympics, games, tokyo, olympic 
 Topic 44: team, players, nba, game, basketball 
 Topic 45: mirabai, medal, olympic, chanu, weightlifting 
 Topic 46: biles, mental, athletes, world, health 
 Topic 47: medal, bronze, gold, punia, tokyo 
 Topic 48: hockey, team, olympics, women's, salima 
 Topic 49: india, pool, will, indian, team 
 Topic 50: olympics, indian, hockey, women's, best 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 11 (approx. per word bound = -6.394, relative change = 1.906e-04) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 12 (approx. per word bound = -6.393, relative change = 1.409e-04) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 13 (approx. per word bound = -6.392, relative change = 1.230e-04) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 14 (approx. per word bound = -6.392, relative change = 9.795e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 15 (approx. per word bound = -6.391, relative change = 8.202e-05) 
Topic 1: india, hockey, olympics, tokyo, match 
 Topic 2: manika, olympics, will, back, tokyo 
 Topic 3: women's, ist, will, men's, day 
 Topic 4: athletes, rs, lakh, will, village 
 Topic 5: sports, hockey, city, india, like 
 Topic 6: hockey, medal, team, bronze, indian 
 Topic 7: sindhu, olympics, pv, tokyo, 2020 
 Topic 8: sports, medal, olympics, us, performance 
 Topic 9: hockey, women, girls, team, even 
 Topic 10: hockey, team, indian, academy, madhya 
 Topic 11: osaka, open, tokyo, world, last 
 Topic 12: gold, medal, olympics, india, won 
 Topic 13: hockey, indian, olympic, sport, medal 
 Topic 14: mirabai, win, samantha, indian, @pvsindhu1 
 Topic 15: road, medal, will, bjp, chief 
 Topic 16: hockey, medal, father, singh, team 
 Topic 17: team, india, hockey, women's, olympics 
 Topic 18: olympics, age, years, bronze, medal 
 Topic 19: team, hockey, indian, women's, match 
 Topic 20: pooja, sonam, ichrak, winner, round 
 Topic 21: sindhu, yamaguchi, win, badminton, first 
 Topic 22: games, olympics, women, tokyo, medal 
 Topic 23: hockey, medal, india, bronze, match 
 Topic 24: sharath, long, mary, world, olympic 
 Topic 25: sports, olympics, women, athletes, will 
 Topic 26: award, dhyan, ratna, chand, khel 
 Topic 27: india, argentina, australia, hockey, team 
 Topic 28: borgohain, lovlina, boxing, medal, boxer 
 Topic 29: gold, medal, chanu, mirabai, tokyo 
 Topic 30: coach, team, india, medal, tokyo 
 Topic 31: indian, singh, tokyo, olympics, india 
 Topic 32: das, team, jadhav, set, 10s 
 Topic 33: shared, video, olympics, brand, sindhu 
 Topic 34: rs, hockey, olympics, singh, minister 
 Topic 35: aditi, golf, medal, olympics, ashok 
 Topic 36: india, penalty, first, minutes, quarter 
 Topic 37: men's, match, team, indian, round 
 Topic 38: hockey, family, caste, team, village 
 Topic 39: sindhu, won, medal, game, world 
 Topic 40: modi, pm, minister, country, india 
 Topic 41: team, hockey, khan, india, women's 
 Topic 42: india, singh, penalty, goal, team 
 Topic 43: athletes, olympics, games, tokyo, olympic 
 Topic 44: team, players, nba, game, basketball 
 Topic 45: mirabai, medal, olympic, chanu, weightlifting 
 Topic 46: biles, mental, athletes, world, health 
 Topic 47: medal, bronze, gold, punia, tokyo 
 Topic 48: hockey, team, olympics, women's, simdega 
 Topic 49: india, pool, will, indian, team 
 Topic 50: olympics, hockey, indian, women's, best 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 16 (approx. per word bound = -6.391, relative change = 7.257e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 17 (approx. per word bound = -6.390, relative change = 7.349e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 18 (approx. per word bound = -6.390, relative change = 8.323e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 19 (approx. per word bound = -6.389, relative change = 1.046e-04) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 20 (approx. per word bound = -6.388, relative change = 6.153e-05) 
Topic 1: india, hockey, olympics, tokyo, match 
 Topic 2: manika, olympics, will, back, tokyo 
 Topic 3: women's, ist, will, men's, day 
 Topic 4: athletes, rs, lakh, will, village 
 Topic 5: sports, hockey, city, india, like 
 Topic 6: hockey, medal, team, bronze, indian 
 Topic 7: sindhu, olympics, pv, tokyo, 2020 
 Topic 8: sports, medal, olympics, us, performance 
 Topic 9: hockey, women, girls, team, even 
 Topic 10: hockey, team, indian, academy, madhya 
 Topic 11: osaka, open, tokyo, world, last 
 Topic 12: gold, medal, olympics, india, won 
 Topic 13: hockey, indian, olympic, sport, medal 
 Topic 14: mirabai, win, indian, medal, samantha 
 Topic 15: road, medal, will, bjp, chief 
 Topic 16: hockey, medal, singh, father, team 
 Topic 17: team, india, hockey, women's, olympics 
 Topic 18: olympics, age, years, bronze, medal 
 Topic 19: team, hockey, indian, women's, match 
 Topic 20: pooja, sonam, ichrak, winner, round 
 Topic 21: sindhu, yamaguchi, win, badminton, first 
 Topic 22: games, olympics, women, tokyo, medal 
 Topic 23: hockey, medal, india, match, bronze 
 Topic 24: sharath, long, mary, world, games 
 Topic 25: sports, olympics, women, athletes, will 
 Topic 26: award, dhyan, ratna, chand, khel 
 Topic 27: india, argentina, australia, team, hockey 
 Topic 28: borgohain, lovlina, boxing, medal, boxer 
 Topic 29: gold, medal, chanu, tokyo, mirabai 
 Topic 30: coach, team, india, medal, tokyo 
 Topic 31: indian, singh, tokyo, olympics, india 
 Topic 32: das, team, jadhav, set, 10s 
 Topic 33: shared, video, olympics, brand, sindhu 
 Topic 34: rs, hockey, olympics, singh, minister 
 Topic 35: aditi, golf, medal, olympics, ashok 
 Topic 36: india, penalty, first, minutes, quarter 
 Topic 37: men's, match, team, indian, round 
 Topic 38: hockey, family, caste, team, village 
 Topic 39: sindhu, won, medal, game, world 
 Topic 40: modi, pm, minister, country, india 
 Topic 41: team, hockey, khan, india, women's 
 Topic 42: india, singh, penalty, goal, team 
 Topic 43: athletes, olympics, games, tokyo, olympic 
 Topic 44: team, players, nba, game, basketball 
 Topic 45: mirabai, medal, olympic, chanu, weightlifting 
 Topic 46: biles, mental, athletes, world, health 
 Topic 47: medal, bronze, gold, punia, tokyo 
 Topic 48: hockey, team, olympics, women's, simdega 
 Topic 49: india, pool, will, indian, team 
 Topic 50: olympics, hockey, indian, women's, best 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 21 (approx. per word bound = -6.388, relative change = 3.728e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 22 (approx. per word bound = -6.388, relative change = 3.420e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 23 (approx. per word bound = -6.388, relative change = 3.147e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 24 (approx. per word bound = -6.388, relative change = 3.887e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 25 (approx. per word bound = -6.387, relative change = 4.185e-05) 
Topic 1: india, hockey, olympics, tokyo, match 
 Topic 2: manika, olympics, will, back, tokyo 
 Topic 3: ist, women's, will, men's, vs 
 Topic 4: athletes, rs, lakh, will, village 
 Topic 5: sports, hockey, city, india, like 
 Topic 6: hockey, team, medal, bronze, indian 
 Topic 7: sindhu, olympics, tokyo, pv, 2020 
 Topic 8: sports, medal, olympics, us, performance 
 Topic 9: hockey, women, girls, team, even 
 Topic 10: hockey, team, indian, academy, madhya 
 Topic 11: osaka, open, tokyo, world, last 
 Topic 12: gold, medal, olympics, india, won 
 Topic 13: hockey, indian, olympic, sport, medal 
 Topic 14: win, mirabai, medal, indian, pv 
 Topic 15: road, medal, will, chief, bjp 
 Topic 16: hockey, medal, father, singh, team 
 Topic 17: team, india, hockey, women's, olympics 
 Topic 18: olympics, age, years, bronze, medal 
 Topic 19: team, hockey, indian, women's, match 
 Topic 20: pooja, sonam, ichrak, winner, round 
 Topic 21: sindhu, yamaguchi, win, badminton, first 
 Topic 22: games, olympics, women, tokyo, medal 
 Topic 23: hockey, medal, india, match, bronze 
 Topic 24: sharath, long, mary, world, games 
 Topic 25: sports, olympics, women, athletes, will 
 Topic 26: award, dhyan, ratna, chand, khel 
 Topic 27: india, australia, argentina, team, hockey 
 Topic 28: borgohain, lovlina, boxing, medal, boxer 
 Topic 29: gold, medal, chanu, tokyo, olympics 
 Topic 30: coach, team, india, medal, tokyo 
 Topic 31: indian, singh, tokyo, olympics, india 
 Topic 32: das, team, jadhav, set, 10s 
 Topic 33: shared, video, olympics, gold, brand 
 Topic 34: hockey, rs, olympics, singh, minister 
 Topic 35: aditi, golf, medal, olympics, ashok 
 Topic 36: india, penalty, first, minutes, quarter 
 Topic 37: indian, match, men's, air, team 
 Topic 38: hockey, family, caste, team, village 
 Topic 39: sindhu, won, medal, game, world 
 Topic 40: modi, pm, minister, country, india 
 Topic 41: team, hockey, khan, india, women's 
 Topic 42: india, penalty, singh, goal, team 
 Topic 43: athletes, olympics, games, tokyo, olympic 
 Topic 44: team, players, nba, game, basketball 
 Topic 45: mirabai, medal, olympic, chanu, weightlifting 
 Topic 46: biles, mental, athletes, world, health 
 Topic 47: medal, bronze, gold, punia, tokyo 
 Topic 48: hockey, team, olympics, women's, simdega 
 Topic 49: india, pool, will, indian, team 
 Topic 50: olympics, hockey, indian, women's, best 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 26 (approx. per word bound = -6.387, relative change = 3.064e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 27 (approx. per word bound = -6.387, relative change = 3.219e-05) 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 28 (approx. per word bound = -6.387, relative change = 3.165e-05) 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 29 (approx. per word bound = -6.386, relative change = 3.148e-05) 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 30 (approx. per word bound = -6.386, relative change = 1.461e-05) 
Topic 1: india, hockey, olympics, tokyo, match 
 Topic 2: manika, olympics, will, back, tokyo 
 Topic 3: ist, women's, will, men's, vs 
 Topic 4: athletes, rs, lakh, will, village 
 Topic 5: sports, hockey, city, india, like 
 Topic 6: hockey, team, medal, bronze, indian 
 Topic 7: sindhu, olympics, tokyo, pv, 2020 
 Topic 8: sports, medal, olympics, us, performance 
 Topic 9: hockey, women, girls, team, even 
 Topic 10: hockey, team, indian, academy, madhya 
 Topic 11: osaka, open, tokyo, world, last 
 Topic 12: gold, medal, olympics, india, won 
 Topic 13: hockey, indian, olympic, sport, medal 
 Topic 14: win, mirabai, medal, indian, proud 
 Topic 15: road, medal, will, chief, minister 
 Topic 16: hockey, medal, father, singh, team 
 Topic 17: team, india, hockey, women's, olympics 
 Topic 18: olympics, age, years, bronze, medal 
 Topic 19: team, hockey, indian, women's, match 
 Topic 20: pooja, sonam, ichrak, winner, round 
 Topic 21: sindhu, yamaguchi, win, badminton, first 
 Topic 22: games, olympics, women, tokyo, medal 
 Topic 23: hockey, medal, india, match, bronze 
 Topic 24: sharath, long, mary, world, games 
 Topic 25: sports, olympics, women, athletes, will 
 Topic 26: award, dhyan, ratna, chand, khel 
 Topic 27: india, australia, argentina, hockey, team 
 Topic 28: borgohain, lovlina, boxing, medal, boxer 
 Topic 29: gold, medal, chanu, tokyo, olympics 
 Topic 30: coach, team, india, medal, tokyo 
 Topic 31: indian, singh, tokyo, olympics, india 
 Topic 32: das, team, jadhav, set, 10s 
 Topic 33: shared, video, olympics, gold, brand 
 Topic 34: hockey, olympics, rs, singh, team 
 Topic 35: aditi, golf, medal, olympics, ashok 
 Topic 36: india, penalty, first, minutes, quarter 
 Topic 37: indian, match, air, men's, round 
 Topic 38: hockey, family, caste, team, village 
 Topic 39: sindhu, won, medal, game, world 
 Topic 40: modi, pm, minister, country, india 
 Topic 41: team, hockey, khan, india, women's 
 Topic 42: india, penalty, singh, goal, team 
 Topic 43: athletes, olympics, games, tokyo, olympic 
 Topic 44: team, players, nba, game, basketball 
 Topic 45: mirabai, medal, olympic, chanu, weightlifting 
 Topic 46: biles, mental, athletes, world, health 
 Topic 47: medal, bronze, gold, punia, tokyo 
 Topic 48: hockey, team, olympics, women's, simdega 
 Topic 49: india, pool, will, indian, team 
 Topic 50: olympics, hockey, indian, women's, best 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 31 (approx. per word bound = -6.386, relative change = 4.555e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 32 (approx. per word bound = -6.386, relative change = 3.089e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 33 (approx. per word bound = -6.386, relative change = 3.027e-05) 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 34 (approx. per word bound = -6.386, relative change = 2.717e-05) 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 35 (approx. per word bound = -6.385, relative change = 2.255e-05) 
Topic 1: india, hockey, olympics, tokyo, match 
 Topic 2: manika, olympics, will, back, tokyo 
 Topic 3: ist, women's, men's, will, vs 
 Topic 4: athletes, rs, lakh, will, village 
 Topic 5: sports, hockey, city, india, like 
 Topic 6: hockey, team, medal, bronze, indian 
 Topic 7: sindhu, olympics, tokyo, pv, 2020 
 Topic 8: sports, medal, olympics, us, performance 
 Topic 9: hockey, women, girls, team, even 
 Topic 10: hockey, team, indian, academy, madhya 
 Topic 11: osaka, open, tokyo, world, last 
 Topic 12: gold, medal, olympics, india, won 
 Topic 13: hockey, indian, olympic, sport, medal 
 Topic 14: win, medal, mirabai, proud, indian 
 Topic 15: road, medal, will, chief, minister 
 Topic 16: hockey, medal, father, singh, team 
 Topic 17: team, india, hockey, women's, olympics 
 Topic 18: olympics, age, years, bronze, medal 
 Topic 19: team, hockey, indian, women's, modi 
 Topic 20: pooja, sonam, ichrak, winner, round 
 Topic 21: sindhu, yamaguchi, win, badminton, first 
 Topic 22: games, olympics, women, tokyo, medal 
 Topic 23: hockey, medal, india, match, bronze 
 Topic 24: sharath, long, mary, world, games 
 Topic 25: sports, olympics, women, athletes, will 
 Topic 26: award, dhyan, ratna, chand, khel 
 Topic 27: india, australia, argentina, hockey, team 
 Topic 28: borgohain, lovlina, boxing, medal, boxer 
 Topic 29: gold, medal, chanu, tokyo, olympics 
 Topic 30: coach, team, india, medal, tokyo 
 Topic 31: indian, singh, tokyo, olympics, india 
 Topic 32: das, team, jadhav, set, 10s 
 Topic 33: shared, video, olympics, gold, brand 
 Topic 34: hockey, olympics, rs, singh, team 
 Topic 35: aditi, golf, medal, olympics, ashok 
 Topic 36: india, penalty, first, minutes, quarter 
 Topic 37: indian, match, air, men's, round 
 Topic 38: hockey, family, caste, team, village 
 Topic 39: sindhu, won, game, medal, world 
 Topic 40: modi, pm, minister, country, india 
 Topic 41: team, hockey, khan, india, women's 
 Topic 42: india, penalty, singh, goal, team 
 Topic 43: athletes, olympics, games, tokyo, olympic 
 Topic 44: team, players, nba, game, basketball 
 Topic 45: mirabai, medal, olympic, chanu, weightlifting 
 Topic 46: biles, mental, athletes, world, health 
 Topic 47: medal, bronze, gold, punia, tokyo 
 Topic 48: hockey, team, olympics, women's, simdega 
 Topic 49: india, pool, will, indian, team 
 Topic 50: olympics, hockey, indian, women's, best 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 36 (approx. per word bound = -6.385, relative change = 1.667e-05) 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 37 (approx. per word bound = -6.385, relative change = 1.328e-05) 
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Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 38 (approx. per word bound = -6.385, relative change = 1.476e-05) 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 39 (approx. per word bound = -6.385, relative change = 1.592e-05) 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 40 (approx. per word bound = -6.385, relative change = 1.340e-05) 
Topic 1: india, hockey, olympics, tokyo, match 
 Topic 2: manika, olympics, will, back, tokyo 
 Topic 3: ist, women's, men's, will, vs 
 Topic 4: athletes, rs, lakh, will, village 
 Topic 5: sports, hockey, city, india, like 
 Topic 6: hockey, team, medal, bronze, indian 
 Topic 7: sindhu, olympics, tokyo, pv, 2020 
 Topic 8: sports, medal, olympics, us, performance 
 Topic 9: hockey, women, girls, team, even 
 Topic 10: hockey, team, indian, academy, madhya 
 Topic 11: osaka, open, tokyo, world, last 
 Topic 12: gold, medal, olympics, india, won 
 Topic 13: hockey, indian, olympic, sport, medal 
 Topic 14: win, medal, mirabai, proud, indian 
 Topic 15: road, medal, will, chief, minister 
 Topic 16: hockey, medal, father, singh, team 
 Topic 17: team, india, hockey, women's, olympics 
 Topic 18: olympics, age, years, bronze, medal 
 Topic 19: team, hockey, indian, women's, modi 
 Topic 20: pooja, sonam, ichrak, winner, round 
 Topic 21: sindhu, yamaguchi, win, badminton, first 
 Topic 22: games, olympics, women, tokyo, medal 
 Topic 23: hockey, match, medal, india, will 
 Topic 24: sharath, long, mary, world, games 
 Topic 25: sports, olympics, women, athletes, will 
 Topic 26: award, dhyan, ratna, chand, khel 
 Topic 27: india, australia, argentina, hockey, team 
 Topic 28: borgohain, lovlina, boxing, medal, boxer 
 Topic 29: gold, medal, chanu, tokyo, olympics 
 Topic 30: coach, team, india, medal, tokyo 
 Topic 31: indian, singh, tokyo, olympics, india 
 Topic 32: das, team, jadhav, set, 10s 
 Topic 33: shared, video, olympics, gold, brand 
 Topic 34: hockey, olympics, rs, singh, team 
 Topic 35: aditi, golf, medal, olympics, ashok 
 Topic 36: india, penalty, first, minutes, quarter 
 Topic 37: indian, match, air, men's, round 
 Topic 38: hockey, family, caste, team, village 
 Topic 39: sindhu, won, game, medal, match 
 Topic 40: modi, pm, minister, country, india 
 Topic 41: team, hockey, khan, india, women's 
 Topic 42: india, penalty, singh, goal, team 
 Topic 43: athletes, olympics, games, tokyo, olympic 
 Topic 44: team, players, nba, game, basketball 
 Topic 45: mirabai, medal, olympic, chanu, weightlifting 
 Topic 46: biles, mental, athletes, world, health 
 Topic 47: medal, bronze, gold, punia, tokyo 
 Topic 48: hockey, team, olympics, women's, simdega 
 Topic 49: india, pool, will, indian, team 
 Topic 50: olympics, hockey, indian, women's, best 
.....................................................................................................................
Completed E-Step (1 seconds). 
Completed M-Step. 
Completing Iteration 41 (approx. per word bound = -6.385, relative change = 1.144e-05) 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 42 (approx. per word bound = -6.385, relative change = 1.036e-05) 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Completing Iteration 43 (approx. per word bound = -6.385, relative change = 1.110e-05) 
.....................................................................................................................
Completed E-Step (1 seconds). 
Completed M-Step. 
Completing Iteration 44 (approx. per word bound = -6.385, relative change = 1.180e-05) 
.....................................................................................................................
Completed E-Step (0 seconds). 
Completed M-Step. 
Model Converged

plot(differentKs)

Structural Topic model

Labels for each topic

Since it is difficult to interpret using just the labels, I have employed a few different methods in the following sections.

labelTopics(news_stm)

Topic 1 Top Words:
     Highest Prob: india, olympics, team, hockey, belgium, indian, men's 
     FREX: belgium, hendrickx, scored, 3-1, goals, penalty, = 
     Lift: dohmen, #india, =, 1964gold, 2-5, 2.25, 2f 
     Score: belgium, penalty, hendrickx, scored, quarter, corners, = 
Topic 2 Top Words:
     Highest Prob: rs, lakh, team, will, indian, hockey, tokyo 
     FREX: lakh, rs, cash, dholakia, ioa, announced, reward 
     Lift: @savjidholakia, adhere, assistance, bearers, clubbed, communicated, halls 
     Score: lakh, rs, cash, dholakia, ioa, ceremony, award 
Topic 3 Top Words:
     Highest Prob: olympics, tokyo, manika, coach, will, back, women's 
     FREX: asci, ads, harmeet, krittwika, violation, permission, manika's 
     Lift: batra's, fukushima, paranjape, trajdos, #tokyo2020withindia_allsports, @india_allsports, @mygovindia 
     Score: manika, asci, ads, harmeet, krittwika, manika's, violation 
Topic 4 Top Words:
     Highest Prob: sports, athletes, india, hockey, olympics, like, city 
     FREX: racing, mangaluru, nagpur, trichy, water, schools, manikandan 
     Lift: #tonsofweight, @ddsportschannel, 2.0, 2.31, 2.68, 202-kg, 2030 
     Score: racing, water, brands, mangaluru, nagpur, trichy, manipur 
Topic 5 Top Words:
     Highest Prob: singh, hockey, medal, team, india, indian, bronze 
     FREX: hardik, punjab, sreejesh, father, lalit, simranjeet, varanasi 
     Lift: 1983, acknowledge, aloo, amarbir, balwinder, demean, furk 
     Score: hardik, punjab, sreejesh, germany, singh, lalit, simranjeet 
Topic 6 Top Words:
     Highest Prob: indian, two, das, world, first, games, olympics 
     FREX: nandu, natekar, 10s, das, kazakhstan, rai, shetty 
     Lift: @anandmahindra, @hvgoenka, 10-10, 10-10-10, 10-10-9, 18s, 1959 
     Score: das, 10s, nandu, natekar, jadhav, panghal, shetty 
Topic 7 Top Words:
     Highest Prob: sindhu, pv, olympics, medal, bronze, win, won 
     FREX: sindhu, bing, pv, tai, @pvsindhu1, smash, jiao 
     Lift: #pvsindhu, @taapsee, chiranjeevi, crosscourt, dulquer, jain, mahesh 
     Score: sindhu, tai, @pvsindhu1, pv, bing, google, tzu-ying 
Topic 8 Top Words:
     Highest Prob: hockey, team, players, medal, olympics, indian, singh 
     FREX: pradesh, madhya, ayodhya, biren, academy, vivek, odisha 
     Lift: 370, astroturf, bhoomi, hon'ble, itarsi, jagbir, patnaik 
     Score: pradesh, madhya, academy, vivek, biren, ayodhya, odisha 
Topic 9 Top Words:
     Highest Prob: biles, osaka, world, mental, tokyo, health, first 
     FREX: vondrousova, zverev, osaka, busta, carreno, biles, marketa 
     Lift: 3-6, belinda, bencic, cilic, conferences, countrymen, dange 
     Score: biles, osaka, djokovic, mental, health, vondrousova, slam 
Topic 10 Top Words:
     Highest Prob: shared, video, wrote, india, olympics, mirabai, olympic 
     FREX: user, pizza, video, vidya, clip, cameraman, cockroach 
     Lift: tiranga, vaccines, #dabbooratnanicalendar, #mirabai, #silver, @neeraj____chopra, @s6ntispam 
     Score: video, user, vidya, pizza, cameraman, clip, cockroach 
Topic 11 Top Words:
     Highest Prob: gold, medal, olympics, tokyo, medals, india, bronze 
     FREX: chopra, ravi, neeraj, dahiya, javelin, anu, malik 
     Lift: mongolian, nurislam, #10084, #56490, #56832, #57340, #65039 
     Score: chopra, neeraj, javelin, ravi, punia, dahiya, airport 
Topic 12 Top Words:
     Highest Prob: will, tokyo, athletes, games, india, village, covid-19 
     FREX: yediyurappa, cdms, taliban, road, bjp, party, afghan 
     Lift: afghan, -with, #56399, @annakiesenhofer, @bhagat_mallika, @kiranshaw, 1000 
     Score: yediyurappa, cdms, taliban, bjp, road, party, cases 
Topic 13 Top Words:
     Highest Prob: team, hockey, india, indian, olympics, women's, britain 
     FREX: savita, rayer, sushila, rampal, salima, visa, associations 
     Lift: 16-man, 29-yearold, 4-4.5, 5-1, 52nd, accuracy, aday 
     Score: savita, visa, brands, salima, papa, sushila, brand 
Topic 14 Top Words:
     Highest Prob: hockey, match, india, will, tokyo, vs, olympics 
     FREX: vs, live, sonyliv, streaming, britain, begin, semifinal 
     Lift: 10km, 4.08, 5-12, 5.30, admirably, akmataliev, arrangements 
     Score: vs, sonyliv, streaming, britain, live, semifinal, argentina 
Topic 15 Top Words:
     Highest Prob: olympics, aditi, world, olympic, golf, athletes, medal 
     FREX: nelly, birdies, korda, aditi, golf, holes, 72 
     Lift: 17-under, arbitration, ashok's, bogeys, carded, inami, koerstz 
     Score: aditi, golf, holes, ashok, fairness, birdies, nelly 
Topic 16 Top Words:
     Highest Prob: round, men's, women's, team, indian, olympics, ist 
     FREX: bhaker, qualification, ist, laser, 10m, pistol, deepika 
     Lift: 0-7, 00pm, 01, 02, 02.73, 03.77, 04 
     Score: ist, round, bhaker, 10m, pistol, qualification, deepika 
Topic 17 Top Words:
     Highest Prob: team, hockey, indian, india, medal, women's, win 
     FREX: beniwal, marijne, khan, chak, rukh, de, shah 
     Lift: bhandarkar, madhur, #jaihind, #menshockeyteam, @iamsrk, @sjoerdmarijne, bhatia 
     Score: rukh, khan, beniwal, chak, shah, marijne, haan 
Topic 18 Top Words:
     Highest Prob: women, olympics, sports, athletes, olympic, tokyo, games 
     FREX: kerala, kerala's, usha, hair, wear, women, san 
     Lift: anti-feminist, -itbegan, @abaisse_burdock, @kasulisk, @sangjungsim, @tokyo2020ko, 0.01 
     Score: kerala, hair, kerala's, usha, beach, anti-feminist, malayali 
Topic 19 Top Words:
     Highest Prob: match, sharath, win, long, game, us, really 
     FREX: sharath, mathias, novak, ma, really, soumyadeep, 11-8 
     Lift: 11-9, 2-11, 5-11, 7-11, 9-11, bai, egg 
     Score: sharath, mathias, novak, soumyadeep, ma, bai, djokovic 
Topic 20 Top Words:
     Highest Prob: family, village, hockey, team, caste, men, casteist 
     FREX: allegedly, vandana's, arrested, castes, caste, casteist, abuses 
     Lift: 504, casteism, intentional, provoke, station, #dalitlivesmatter, #iamprouddalit 
     Score: caste, casteist, vandana's, allegedly, arrested, dalit, dalits 
Topic 21 Top Words:
     Highest Prob: award, dhyan, chand, ratna, khel, hockey, major 
     FREX: ratna, dhyan, khel, renamed, chand, gandhi, award 
     Lift: breadth, chand's, farm, icc, length, medallion, vishal 
     Score: ratna, khel, dhyan, chand, award, gandhi, rajiv 
Topic 22 Top Words:
     Highest Prob: india, penalty, team, first, australia, two, argentina 
     FREX: penalty, defence, corner, pool, minute, australia, chances 
     Lift: aussies, barking, casella, ekka, forays, goalless, instructions 
     Score: penalty, corner, argentina, corners, australia, minute, quarter 
Topic 23 Top Words:
     Highest Prob: medal, mirabai, chanu, tokyo, olympics, olympic, first 
     FREX: jerk, zhihui, 115kg, nahin, tha, 87kg, snatch 
     Lift: @nainaarora8, @rahulgandhi, @sandartistmanas, 1.13, 10-rs, 104kg, 106kg 
     Score: mirabai, jerk, snatch, chanu, weightlifting, lift, malleswari 
Topic 24 Top Words:
     Highest Prob: boxing, borgohain, lovlina, medal, olympic, bronze, boxer 
     FREX: sandhya, lovlina's, boxing, lovlina, borgohain, bergamasco, ring 
     Lift: #amul, #bajrangpunia, #ftw, @nivinofficial, 1999, 2002-08, 32-year-old 
     Score: sandhya, boxing, lovlina's, borgohain, lovlina, ring, mary 
Topic 25 Top Words:
     Highest Prob: indian, students, tokyo, olympics, singh, university, student 
     FREX: kiit, amoj, nishad, students, lpu, student, university 
     Lift: amoj, chitkara, nishad, paralympics, titled, 3p, 4x400 
     Score: students, kiit, lpu, university, amoj, nishad, selected

Estimating the relationship between the topics and the metadata

The graph below illustrates much more(or less) the topic is mentioned when the article is tagged as Women.
It does not give any insightful results because it shows that the sports that had women athletes in them were mentioned more when the article was tagged as women and sports that had men athletes were mentioned more when the article was tagged as men; which is obvious.

modelEffects <- estimateEffect(formula = 1:k ~ Gender,
                               stmobj = news_stm,
                               metadata = df_final)

plot(modelEffects, covariate = "Gender", topics = c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25), model = news_stm, method = "difference", cov.value1 = 1, cov.value2 = 0, xlab = "Men...Women", main = "Olympics Topics discussing Men's/Women's Sports", xlim = c(-0.2, 0.2), labeltype = "custom", custom.labels = c("1.HockeyDetails","2.CashPrizes","3.TableTennisWomen's","4.NotOlympicsRelated1","5.HockeyAwards","6.Archery&OtherSports","7.BadmintonSindhu","8.HockeyRewards","9.InternationalPlayers","10.Media","11.WrestlingandJavelinThrow (Men's)","12.NotOlympicsRelated2","13.HockeyInfo","14.HockeySchedule","15.AditiGolf","16.ShootingSport","17.HockeyCongratulatoryMessages","18.NotOlympicsRelated3","19.TableTennisMen's","20.CasteAndWomen'sHockey","21.KhelRatnaAward","22.HockeyDetails2,","23.MirabaiWeightlifting","24.BoxingLovlina","25.LPUStudentsatOlympics"))

Correlation Plot

The plot shows that none of the topics are correlated which was unexpected especially since many of the topics pertained to the Indian Hockey team.

mod.out.corr <- topicCorr(news_stm,method = c("simple"), cutoff = 0.01, verbose = TRUE)
plot(mod.out.corr)

Structural Topic Modelling with Topical Content

I added a topical content covariate to the structural topic model to check for differences in the words used. However, this model was taking a long time to run so I decided not to use it for the analysis.

ContentNews <- stm(news_dfm_stm, K = 25, prevalence =~ Gender, content =~ Gender, max.em.its = 5, seed = 1234,data =df_final, init.type = "Spectral")

Beginning Spectral Initialization 
     Calculating the gram matrix...
     Using only 10000 most frequent terms during initialization...
     Finding anchor words...
    .........................
     Recovering initialization...
    ....................................................................................................
Initialization complete.
.....................................................................................................................
Completed E-Step (0 seconds). 
....................................................................................................
Completed M-Step (83 seconds). 
Completing Iteration 1 (approx. per word bound = -7.715) 
.....................................................................................................................
Completed E-Step (0 seconds). 
....................................................................................................
Completed M-Step (80 seconds). 
Completing Iteration 2 (approx. per word bound = -7.081, relative change = 8.223e-02) 
.....................................................................................................................
Completed E-Step (0 seconds). 
....................................................................................................
Completed M-Step (180 seconds). 
Completing Iteration 3 (approx. per word bound = -6.895, relative change = 2.617e-02) 
.....................................................................................................................
Completed E-Step (0 seconds). 
....................................................................................................
Completed M-Step (184 seconds). 
Completing Iteration 4 (approx. per word bound = -6.828, relative change = 9.714e-03) 
.....................................................................................................................
Completed E-Step (0 seconds). 
....................................................................................................
Completed M-Step (181 seconds). 
Model Terminated Before Convergence Reached

labelTopics(ContentNews)

Topic Words:
 Topic 1: twitterati, penalty, 2-3, scoreline, conceding, semifinal, corners 
 Topic 2: lakh, cash, rs, office, named, kom, respective 
 Topic 3: sound, europe, album, kiren, paddler, mukherjee, rijiju 
 Topic 4: platforms, seasoned, campaigns, short-term, visibility, promotions, lifestyle 
 Topic 5: gurmail, slotted, mohali, happiness, sukhvir, process, jalandhar 
 Topic 6: 9s, chi-lin, hyek, jin, blichfeldt, mia, gideon 
 Topic 7: #pvsindhu, dulquer, salmaan, steeply, mahesh, @pvsindhu1, @taapsee 
 Topic 8: 500, astroturf, 80, trials, madhya, listed, bhopal 
 Topic 9: medvedev, busta, carreno, 3-6, karen, khachanov, daniil 
 Topic 10: tiranga, featured, actor, awestruck, sharma, anushka, sunday 
 Topic 11: nurislam, zavur, 13-2, 121, bulgaria's, helsinki, amine 
 Topic 12: funds, resigned, agenda, write, principal, reports, polls 
 Topic 13: replace, understanding, knowing, focusing, interesting, understand, form 
 Topic 14: aired, commentary, scorecard, broadcast, indiamen's, 00, streaming 
 Topic 15: labelled, 66, 72, federations, professionals, halfway, oldest 
 Topic 16: divyansh, bhaker, saravanan, manu, angad, 08, 49er 
 Topic 17: pouring, rukh, srk, hockeyroos, script, emojis, @iamsrk 
 Topic 18: fundamentally, realising, european, largest, system, archer, excellence 
 Topic 19: chirag, ma, nail, tooth, uphill, struggled, soumyadeep 
 Topic 20: sc, crackers, mothers, complaint, alleged, mockery, fir 
 Topic 21: chand's, respecting, fitting, ratna, khel, requests, foremost 
 Topic 22: wasted, seoul, runners-up, min, regained, lower-ranked, barking 
 Topic 23: al-rashidi, 87kg, arsenal, jerk, 202, set-up, 115kg 
 Topic 24: sustaining, southpaw, pugilist, lovlina's, nien-chin, kom's, borgohain's 
 Topic 25: jump, relay, jacob, whatever, neeraj, chopra, race 
 
 Covariate Words:
 Group 0: fond, surprising, beginning, men's, congratulatory, homework, veteran 
 Group 1: equal, supported, prepared, never, walked, girl, striking 
 
 Topic-Covariate Interactions:
 Topic 1, Group 0: guests, afwa, numerous, awaited, battling, loick, somaya 
 Topic 1, Group 1: denying, dragflicker, 3-0, 03, 59, first-time, hard-earned 
 
 Topic 2, Group 0: campus, dining, avoid, flag-bearers, narinder, gurung, participants 
 Topic 2, Group 1: diamond, dholakia, hari, savji, hk, krishna, incentive 
 
 Topic 3, Group 0: funniest, priority, itf, adani, ride, mature, thereafter 
 Topic 3, Group 1: permission, table-tennis, asci, ads, violation, batra's, paranjape 
 
 Topic 4, Group 0: narrative, lalremsiami, wonder, sponsoring, adds, parent, enable 
 Topic 4, Group 1: shiva, tripura, probe, racing, mangaluru, nagpur, trichy 
 
 Topic 5, Group 0: witnessing, initially, giants, lockdown, virender, executed, houses 
 Topic 5, Group 1: forays, rewarded, reducing, stops, backs, sahara, kd 
 
 Topic 6, Group 0: 88, koreans, ease, 56, breathed, ksenia, natekar 
 Topic 6, Group 1: firing, guru, comment, sparring, indonesians, sukamuljo, delta 
 
 Topic 7, Group 0: 52, wrist, ultra, xiaomi, mi, smartphone, gesture 
 Topic 7, Group 1: baroda, crosscourt, sharechat, bwf, ravipudi, google, hd 
 
 Topic 8, Group 0: ram, laying, studies, windows, marginalised, referred, grewal 
 Topic 8, Group 1: khunti, meals, proper, everyday, trainers, mujhe, bamboo 
 
 Topic 9, Group 0: resulted, martin, clinching, gaze, clocked, brink, troika 
 Topic 9, Group 1: robbins, sally, scary, lit, osaka's, conferences, flame 
 
 Topic 10, Group 0: tripura, dance, vaccines, effective, market, farmers, opinion 
 Topic 10, Group 1: showered, increasing, precious, samantha, tagged, guardian, charming 
 
 Topic 11, Group 0: track-and-field, applauded, berlin, #55357, kd, 1900, airport 
 Topic 11, Group 1: 91, 88, grip, sonam, stretched, medalled, brigade 
 
 Topic 12, Group 0: probe, trumped, fears, correct, son's, investigation, cdms 
 Topic 12, Group 1: leadership, biswa, himanta, sarma, b.s, command, elections 
 
 Topic 13, Group 0: trust, 4-5, criteria, proper, philosophy, importance, selection 
 Topic 13, Group 1: soaring, belt, rebound, sides, shocked, halfback, hollie 
 
 Topic 14, Group 0: belgiummen's, bout, thereby, niyazbekov, features, theindia, clock 
 Topic 14, Group 1: contribution, shahabad, daughters, applauded, praised, glued, 2-0 
 
 Topic 15, Group 0: also-rans, parallel, pipped, sportswomen, lodged, quiet, band 
 Topic 15, Group 1: 69, 67, 68, pentathlon, banned, zealand's, developing 
 
 Topic 16, Group 0: desired, sonam, onwards, 18th, gagan, wonders, k 
 Topic 16, Group 1: bronze-medallist, clocked, timing, ksenia, equestrian, patel, polikarpova 
 
 Topic 17, Group 0: rewriting, ravipudi, baroda, imagination, thanking, trip, erstwhile 
 Topic 17, Group 1: project, lalremsiami, parallel, reins, 2007, scenes, kabir 
 
 Topic 18, Group 0: base, sections, tip, nature, fate, saina, nerve 
 Topic 18, Group 1: streak, contributions, x, lens, awardees, study, enable 
 
 Topic 19, Group 0: brothers, shocked, 11-6, bai, mathias, boe, 2-11 
 Topic 19, Group 1: dining, reclaimed, arrival, heroics, normal, informed, student 
 
 Topic 20, Group 0: hail, hardik's, mithapur, truck, khusropur, sweets, mla 
 Topic 20, Group 1: tip, campus, chauhan, security, gesture, spanish, lodged 
 
 Topic 21, Group 0: patel, 91, nba, lens, awardees, study, stops 
 Topic 21, Group 1: bcci, cement, heavyweights, vishal, jantar, mantar, farm 
 
 Topic 22, Group 0: toe-to-toe, brigade, medalled, stretched, denying, solitary, ticked 
 Topic 22, Group 1: fate, martin, defined, dragflicker, furious, noel, concentration 
 
 Topic 23, Group 0: 57-year, dope, zhizhi, bentinidis, malikov, bartonietz, hohn 
 Topic 23, Group 1: toh, perfection, register, pad, saina, mere, k 
 
 Topic 24, Group 0: stitches, jalolov, ads, violation, asci, gutsy, bicky 
 Topic 24, Group 1: box, cagey, planning, @lovlinaborgohai, exhibition, cakiroglu, mary's 
 
 Topic 25, Group 0: dutee, lpu, exhibition, sreeshankar, universities, lovely, shivpal 
 Topic 25, Group 1: goalpost, goalkeeper's, massive, tamberi, seat, scream, gratitude

Although I will not be utilising this model, I was curious to see if there was a difference in the words used for each gender’s sports event so I plotted the words for a few topics.There was no significant difference as the terms used for both pertained to information about the match or the medals won.

plot(ContentNews, type = "summary",xlim=c(0,0.5))

plot(ContentNews,type="perspectives", topics=1)

plot(ContentNews,type="perspectives", topics=7)

plot(ContentNews,type="perspectives", topics=17)

After running the structural topic model, I decided not to use this for my analysis because of the following reasons:

The model is not producing anything insightful because it provides the information that women who played particular sports are mentioned in women’s section and vice versa, but the terms used to describe the events are not present.

2. This model becomes computationally expensive when a topical content covariate is added.

In my next blog post, I will be using LDA topic models on women’s and men’s corpora separately.

Reference: Warin, T. (2020). Structural Topic Models: stm R package. https://warin.ca/shiny/stm/#section-the-structural-topic-model