Detecting Anxiety through Reddit 论文

摘要

Previous investigations into detecting mental illnesses through social media have predominately focused on detecting depression through Twitter corpora In this paper, we study anxiety disorders through personal narratives collected through the popular social media website, Reddit. We build a substantial data set of typical and anxietyrelated posts, and we apply N -gram language modeling, vector embeddings, topic analysis, and emotional norms to generate features that accurately classify posts related to binary levels of anxiety. We achieve an accuracy of 91% with vectorspace word embeddings, and an accuracy of 98% when combined with lexiconbased features.