Fig 1.
Three types of unmet information needs: lack of responses, inaccurate information, and outdated information.
Table 1.
r/f1visa data overview.
Table 2.
Post dataset examples.
Table 3.
Comment dataset examples.
Table 4.
Coherence scores per number of topics.
Table 5.
Topics among posts of individuals who posted two or more times before the COVID-19 pandemic.
Table 6.
Topics among posts of individuals who posted two or more times during the COVID-19 pandemic.
Fig 2.
Number of questions before and during the COVID-19 pandemic.
(a) shows the ratio of authors who posted a specific number of times compared to the total number of authors before COVID-19. (b) presents the same during COVID-19.
Fig 3.
Box plots of cosine similarity.
(a) Plot describing cosine similarity among the posts of individual authors who post more than two posts BEFORE the COVID-19. (b) Plot describing cosine similarity among posts of individual authors who posted more than two posts DURING the COVID-19.
Table 7.
Ratio of self-commenting to the number of posts.
Fig 4.
Examples of a case that is resolved with a single post (left) and a case that remains unresolved after two posts (right).