Wordcloud of Q12 top 100 words

Sentiment analysis of Q12 (1)

Sentiment analysis of Q12 (2)

A biterm is defined as a pair of words co-occurring in the same text window. If you have as an example a document with sequence of words 'A B C B', and assuming the window size is set to 3, that implies there are two text windows which can generate biterms namely text window 'A B C' with biterms 'A B', 'B C', 'A C' and text window 'B C B' with biterms 'B C', 'C B', 'B B' A biterm is an unorder word pair where 'B C' = 'C B'. Thus, the document 'A B C B' will have the following biterm frequencies: • ’A B’: 1 • ’B C’: 3 • ’A C’: 1 • ’B B’: 1 These biterms are used to create the model

Decision of the numbers of the topics

Research results of 3 topics

label type = "frex"

FREX: are the words that are both frequent and exclusive, identifying words that distinguish topics.

Research results of 3 topics

label type = "Prob"

Highest Prob: are the words within each topic with the highest probability (inferred directly from topic-word distribution parameter β).

Research results of 3 topics

label type = "Score"

Research results of 3 topics correlation

Research results of 3 document-topic proportions

Research results of topic1 wordcloud

Research results of topic2 wordcloud

Research results of topic3 wordcloud

Research results of topic1 and topic 2 comparision

Research results of topic1 and topic 3 comparision

Research results of topic2 and topic 3 comparision

Research results 4

Using covariate "group" to test the effects on different topics

Research results 5

Using covariate "country" to test the effects on different topics