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Linguistic Markers Indicating Therapeutic Outcomes of Social Media Disclosures of Schizophrenia

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Published:06 December 2017Publication History
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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

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          Publication History

          • Published: 6 December 2017
          Published in pacmhci Volume 1, Issue CSCW

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