Identifying self-disclosed anxiety on Twitter: A natural language processing approach.

Journal: Psychiatry research
PMID: 37956589

Abstract

BACKGROUND: Text analyses of social media posts are a promising source of mental health information. This study used natural language processing to explore distinct language patterns on Twitter related to self-reported anxiety diagnosis.

Authors

  • Daniel Zarate
    College of Health and Biomedicine, Royal Melbourne Institute of Technology (RMIT), Australia. Electronic address: Daniel.zarate@live.vu.edu.au.
  • Michelle Ball
    Institute for Health and Sport, Victoria University, Melbourne, Australia.
  • Maria Prokofieva
    Institute for Health and Sport, Victoria University, Melbourne, Australia.
  • Vassilis Kostakos
    University of Melbourne, Melbourne, Australia.
  • Vasileios Stavropoulos
    College of Health and Biomedicine, Royal Melbourne Institute of Technology (RMIT), Australia; Department of Psychology, University of Athens, Athens, Greece.

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