Why Do They Leave: Modeling Participation in Online Depression Forums

Farig Sadeque, Ted Pedersen, Thamar Solorio, Prasha Shrestha, Nicolas Rey-Villamizar, Steven Bethard

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

Depression is a major threat to public health, accounting for almost 12% of all disabilities and claiming the life of 1 out of 5 patients suffering from it. Since depression is often signaled by decreasing social interaction, we explored how analysis of online health forums may help identify such episodes. We collected posts and replies from users of several forums on healthboards.com and analyzed changes in their use of language and activity levels over time. We found that users in the Depression forum use fewer social words, and have some revealing phrases associated with their last posts (e.g., cut myself). Our models based on these findings achieved 94 F1 for detecting users who will withdraw from a Depression forum by the end of a 1-year observation period.

Original languageEnglish (US)
Title of host publicationEMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings of the 4th International Workshop on Natural Language Processing for Social Media, SocialNLP 2016
PublisherAssociation for Computational Linguistics (ACL)
Pages14-19
Number of pages6
ISBN (Electronic)9781945626326
StatePublished - 2016
Event4th ACM Workshop on Natural Language Processing for Social Media, SocialNLP 2016, associated with the Conference on Empirical Methods in Natural Language Processing, EMNLP 2016 - Austin, United States
Duration: Nov 1 2016Nov 1 2016

Publication series

NameEMNLP 2016 - Conference on Empirical Methods in Natural Language Processing, Proceedings of the 4th International Workshop on Natural Language Processing for Social Media, SocialNLP 2016

Conference

Conference4th ACM Workshop on Natural Language Processing for Social Media, SocialNLP 2016, associated with the Conference on Empirical Methods in Natural Language Processing, EMNLP 2016
Country/TerritoryUnited States
CityAustin
Period11/1/1611/1/16

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems
  • Software
  • Computational Theory and Mathematics

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