lda_tuning.R

result<- FindTopicsNumber(
bios_dtm,
topics= seq(from=5, to=25, by=1),
metrics= c("Griffiths2004", "CaoJuan2009", "Arun2010", "Deveaud2014"),
method="VEM",
control=list(seed=77),
mc.cores=10L,
verbose=TRUE
 )

FindTopicsNumber_plot(result)

bios_lda<- LDA(bios_dtm, k=12, control=list(alpha=0.1, seed=5678), method="VEM")
bios_lda_td<- tidy(bios_lda)

top_terms<-bios_lda_td %>%
 group_by(topic) %>%
 top_n(30, beta) %>%
 ungroup() %>%
 arrange(topic, -beta) %>% 
# mutate(term = text_to_emoji(term)) %>%
 mutate(term= gsub("hashtag", "#", term))

topics_terms<-top_terms %>% 
dplyr::select(-beta) %>% 
# mutate(topic=paste0("t", topic)) %>%
 group_by(topic) %>% 
 summarise(top_10=paste(term, collapse=", ")) %>% 
 ungroup()

topics_terms_levels<- paste0(topics_terms$topic, ": ", topics_terms$top_10)

bios_lda_gamma<- tidy(bios_lda, matrix="gamma") %>%
 rowwise() %>%
 mutate(gamma=gamma+runif(1,0,0.0001))