Phrase-level pairwise topic modeling to uncover helpful peer responses to online suicidal crises

This study characterizes the content of user posts and peer comments on social media regarding suicidal crises and introduces a pairwise topic modeling approach to analyze these interactions. The method models both the generative processes of user posts and peer comments and their associations, using phrases for improved representation. Data from Reddit's r/SuicideWatch was used to examine topic associations and their influence on perceived helpfulness (upvotes). Findings were validated using data from individuals with suicidal ideation history. The study suggests that modeling these associations can uncover helpful peer responses, particularly suggestions of professional help, and the approach is applicable to other paired corpora.

Meng Jiang, Brooke A. Ammerman, Qingkai Zeng, Ross Jacobucci, Alex Brodersen