Predicting Continued Participation in Online Health Forums

Farig Sadeque, Thamar Solorio, Ted Pedersen, Prasha Shrestha, Steven Bethard

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

7 Scopus citations

Abstract

Online health forums provide advice and emotional solace to their users from a social network of people who have faced similar conditions. Continued participation of users is thus critical to their success. In this paper, we develop machine learning models for predicting whether or not a user will continue to participate in an online health forum. The prediction models are trained and tested over a large dataset collected from the support group based social networking site dailystrength.org. We find that our models can predict continued participation with over 83% accuracy after as little as 1 month observing the user's activities, and that performance increases rapidly up to 1 year of observation. We also show that features such as the time since a user's last activity are consistently predictive regardless of the length of the observation period, while other features, such as the number of times a user replies to others, decrease in predictiveness as the observation period grows.

Original languageEnglish (US)
Title of host publicationEMNLP 2015 - 6th International Workshop on Health Text Mining and Information Analysis, LOUHI 2015 - Proceedings of the Workshop
PublisherAssociation for Computational Linguistics (ACL)
Pages12-20
Number of pages9
ISBN (Electronic)9781941643327
StatePublished - 2015
Externally publishedYes
Event6th International Workshop on Health Text Mining and Information Analysis, LOUHI 2015, co-located with EMNLP 2015 - Lisbon, Portugal
Duration: Sep 17 2015 → …

Publication series

NameEMNLP 2015 - 6th International Workshop on Health Text Mining and Information Analysis, LOUHI 2015 - Proceedings of the Workshop

Conference

Conference6th International Workshop on Health Text Mining and Information Analysis, LOUHI 2015, co-located with EMNLP 2015
Country/TerritoryPortugal
CityLisbon
Period9/17/15 → …

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Civil and Structural Engineering
  • Health Informatics

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