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Title: Person-centered Pathways to Care: A Computational Examination of Social Media for Mental Health
Sindhu Kiranmai Ernala
Ph.D. student in Computer Science
School of Interactive Computing
Georgia Institute of Technology
Date: Tuesday, November 26, 2019
Time: 1:00 - 4:00 pm (EST)
Location: Coda C1215 Midtown
Committee:
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Dr. Munmun De Choudhury (Advisor, School of Interactive Computing, Georgia Institute of Technology)
Dr. Eric P. S. Baumer (School of Computer Science andEngineering, Lehigh University)
Dr. Moira Burke (Core Data Science, Facebook)
Dr. Elizabeth Mynatt (Institute for People and Technology, School of Interactive Computing, Georgia Institute of Technology)
Dr. Diyi Yang (School of Interactive Computing, Georgia Institute of Technology)
Abstract:
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Improving the well-being of people with mental illness requires not only clinical treatment but also social support. My research examines the efficacy of social media as a platform supporting both clinical and social care for people with mental illness. To this end, I combine theories from social psychology, computer-mediated communication, and clinical literature with methods from natural language analysis, machine learning, and statistical modeling. Focusing on schizophrenia, one of the most debilitating and stigmatizing of mental illnesses, this thesis contributes a deeper understanding on pathways to care via social media along three themes:
1) online self-disclosure and social support as pathways to social care,
2) prediction of clinical mental health states from social media data to support clinical interventions, and
3) intersection of social and clinical pathways along the course of illness.
My proposed work focuses on the third theme and aims to understand how social and clinical pathways to care intersect during major transitions like hospitalizations. I propose two studies to examine health status transitions as exhibited on social media and online social re-integration mechanisms after stigmatizing hospitalizations. Overall, this work contributes novel methodologies and frameworks to understand the efficacy of social media as a mental health intervention platform; informing clinicians, researchers, and social media designers who engage in developing and deploying interventions.
