Nonparametric discovery of online mental health-related communities

Bo Dao, Thin Nguyen, Svetha Venkatesh, Dinh Phung

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

3 Citations (Scopus)

Abstract

People are increasingly using social media, especially online communities, to discuss mental health issues and seek supports. Understanding topics, interaction, sentiment and clustering structures of these communities informs important aspects of mental health. It can potentially add knowledge to the underlying cognitive dynamics, mood swings patterns, shared interests, and interaction. There has been growing research interest in analyzing online mental health communities; however sentiment analysis of these communities has been largely under-explored. This study presents an analysis of online Live Journal communities with and without mental health-related conditions including depression and autism. Latent topics for mood tags, affective words, and generic words in the content of the posts made in these communities were learned using nonparametric topic modelling. These representations were then input into a nonparametric clustering to discover meta-groups among the communities. The best performance results can be achieved on clustering communities with latent mood-based representation for such communities. The study also found significant differences in usage latent topics for mood tags and affective features between online communities with and without affective disorders. The findings reveal useful insights into hyper-group detection of online mental health-related communities.

Original languageEnglish
Title of host publicationProceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics
EditorsEric Gaussier, Longbing Cao, Patrick Gallinari, James Kwok, Gabriella Pasi , Osmar Zaiane
Place of PublicationPiscataway NJ USA
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages10
ISBN (Electronic)9781467382731
ISBN (Print)9781467382724
DOIs
Publication statusPublished - 2015
Externally publishedYes
EventIEEE International Conference on Data Science and Advanced Analytics 2015 - Paris, France
Duration: 19 Oct 201521 Oct 2015
http://dsaa2015.lip6.fr/

Conference

ConferenceIEEE International Conference on Data Science and Advanced Analytics 2015
Abbreviated titleDSAA 2015
CountryFrance
CityParis
Period19/10/1521/10/15
Internet address

Keywords

  • Mental Health
  • Moods and Emotion
  • Nonparametric Discovery
  • Online Communities
  • Social Media
  • Topics

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