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01-09-2014 | Original Research

Obesity in social media: a mixed methods analysis

Authors: Wen-ying Sylvia Chou, PhD, MPH, Abby Prestin, PhD, Stephen Kunath, MS

Published in: Translational Behavioral Medicine | Issue 3/2014

Abstract

The escalating obesity rate in the USA has made obesity prevention a top public health priority. Recent interventions have tapped into the social media (SM) landscape. To leverage SM in obesity prevention, we must understand user-generated discourse surrounding the topic. This study was conducted to describe SM interactions about weight through a mixed methods analysis. Data were collected across 60 days through SM monitoring services, yielding 2.2 million posts. Data were cleaned and coded through Natural Language Processing (NLP) techniques, yielding popular themes and the most retweeted content. Qualitative analyses of selected posts add insight into the nature of the public dialogue and motivations for participation. Twitter represented the most common channel. Twitter and Facebook were dominated by derogatory and misogynist sentiment, pointing to weight stigmatization, whereas blogs and forums contained more nuanced comments. Other themes included humor, education, and positive sentiment countering weight-based stereotypes. This study documented weight-related attitudes and perceptions. This knowledge will inform public health/obesity prevention practice.

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Title: Obesity in social media: a mixed methods analysis
Authors: Wen-ying Sylvia Chou, PhD, MPH
Abby Prestin, PhD
Stephen Kunath, MS
Publication date: 01-09-2014
Publisher: Springer US
Published in: Translational Behavioral Medicine / Issue 3/2014
Print ISSN: 1869-6716
Electronic ISSN: 1613-9860
DOI: https://doi.org/10.1007/s13142-014-0256-1

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