Research Area:  Machine Learning

Abstract:

Although rates of diagnosing mental illness have improved over the past few decades, many cases remain undetected. Symptoms associated with mental illness are observable on Twitter, Facebook, and web forums, and automated methods are increasingly able to detect depression and other mental illnesses. In this paper, recent studies that aimed to predict mental illness using social media are reviewed. Mentally ill users have been identified using screening surveys, their public sharing of a diagnosis on Twitter, or by their membership in an online forum, and they were distinguishable from control users by patterns in their language and online activity. Automated detection methods may help to identify depressed or otherwise at-risk individuals through the large-scale passive monitoring of social media, and in the future may complement existing screening procedures.

Keywords:  

Author(s) Name:  Sharath Chandra Guntuku, David B Yaden, Margaret L Kern, Lyle H Ungar, Johannes C Eichstaedt

Publisher name:  ELSEVIER

DOI:  10.1016/j.cobeha.2017.07.005

Volume Information:  Volume 18, December 2017, Pages 43-49

Paper Link:   https://www.sciencedirect.com/science/article/pii/S2352154617300384