  We investigate relationships between online self-disclosure and received
social feedback during the COVID-19 crisis. We crawl a total of 2,399 posts and
29,851 associated comments from the r/COVID19_support subreddit and manually
extract fine-grained personal information categories and types of social
support sought from each post. We develop a BERT-based ensemble classifier to
automatically identify types of support offered in users' comments. We then
analyze the effect of personal information sharing and posts' topical, lexical,
and sentiment markers on the acquisition of support and five interaction
measures (submission scores, the number of comments, the number of unique
commenters, the length and sentiments of comments). Our findings show that: 1)
users were more likely to share their age, education, and location information
when seeking both informational and emotional support, as opposed to pursuing
either one; 2) while personal information sharing was positively correlated
with receiving informational support when requested, it did not correlate with
emotional support; 3) as the degree of self-disclosure increased, information
support seekers obtained higher submission scores and longer comments, whereas
emotional support seekers' self-disclosure resulted in lower submission scores,
fewer comments, and fewer unique commenters; 4) post characteristics affecting
social feedback differed significantly based on types of support sought by post
authors. These results provide empirical evidence for the varying effects of
self-disclosure on acquiring desired support and user involvement online during
the COVID-19 pandemic. Furthermore, this work can assist support seekers hoping
to enhance and prioritize specific types of social feedback.
