Disease Coping and Social Adversities Characterize User-Generated Content on Thrive with Me, an mHealth Platform for Men Living with HIV: Implications of a Novel Machine Learning–Aided Thematic Analysis

Virtual · June 2020

Poster Sessions · Clinical Science

Simone Skeen
Hunter College, City University of New York (CUNY)
S. Scott Jones
Hunter College, City University of New York (CUNY)
Carolyn Cruse
Hunter College, City University of New York (CUNY)
AvaGrace Palazzolo
Hunter College, City University of New York (CUNY)
Keith Horvath
San Diego State University

Abstract

Natural language processing and qualitative techniques were used to analyze users’ posts on a peer-support webapp for men living with HIV. Machine-detected topics and human-interpreted themes illustrated the benefits of the webapp, while highlighting the potentially detrimental influence of external news media.

Media/Technology

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Disease Coping and Social Adversities Characterize User-Generated Content on Thrive with Me, an mHealth Platform for Men Living with HIV: Implications of a Novel Machine Learning–Aided Thematic Analysis

Abstract

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