Social Media Mining to Understand Public Mental Health

In this paper, we apply text mining and topic modelling to understand public mental health. We focus on identifying common mental health topics across two anonymous social media platforms: Reddit and a mobile journalling/mood-tracking app. Furthermore, we analyze journals from the app to uncover relationships between topics, journal visibility (private vs. visible to other users of the app), and user-labelled sentiment. Our main findings are that (1) anxiety and depression are shared on both platforms; (2) users of the journalling app keep routine topics such as eating private, and these topics rarely appear on Reddit; and (3) sleep was a critical theme on the journalling app and had an unexpectedly negative sentiment.