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Linguistic Markers Indicating Therapeutic Outcomes of Social Media Disclosures of Schizophrenia

Published: 06 December 2017 Publication History

Abstract

Self-disclosure of stigmatized conditions is known to yield therapeutic benefits. Social media sites are emerging as promising platforms enabling disclosure around a variety of stigmatized concerns, including mental illness. What kind of behavioral changes precede and follow such disclosures? Do the therapeutic benefits of "opening up" manifest in these changes? In this paper, we address these questions by focusing on disclosures of schizophrenia diagnoses made on Twitter. We adopt a clinically grounded quantitative approach to first identify temporal phases around disclosure during which symptoms of schizophrenia are likely to be significant. Then, to quantify behaviors before and after disclosures, we define linguistic measures drawing from literature on psycholinguistics and the socio-cognitive model of schizophrenia. Along with significant linguistic differences before and after disclosures, we find indications of therapeutic outcomes following disclosures, including improved readability and coherence in language, future orientation, lower self preoccupation, and reduced discussion of symptoms and stigma perceptions. We discuss the implications of social media as a new therapeutic tool in supporting disclosures of stigmatized conditions.

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cover image Proceedings of the ACM on Human-Computer Interaction
Proceedings of the ACM on Human-Computer Interaction  Volume 1, Issue CSCW
November 2017
2095 pages
EISSN:2573-0142
DOI:10.1145/3171581
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 06 December 2017
Published in PACMHCI Volume 1, Issue CSCW

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Author Tags

  1. language
  2. mental health
  3. psychiatry
  4. schizophrenia
  5. self-disclosure
  6. social media
  7. therapeutic benefits
  8. twitter

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  • National Institutes of Health

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  • (2024)Detecting Multiple Mental Health Disorders with Large Language Models2024 28th International Conference Information Visualisation (IV)10.1109/IV64223.2024.00051(252-257)Online publication date: 22-Jul-2024
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