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Fat stigma and body objectification: A text analysis approach using social media content

This study investigates how female and male genders are positioned in fat stigmatising discourses that are being conducted over social media. Weight-based linguistic data corpus, extracted from three popular social media (SM) outlets, Twitter, YouTube and Reddit, was examined for fat stigmatising co...

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Autores principales: Wanniarachchi, Vajisha U, Scogings, Chris, Susnjak, Teo, Mathrani, Anuradha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9386857/
https://www.ncbi.nlm.nih.gov/pubmed/35990109
http://dx.doi.org/10.1177/20552076221117404
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author Wanniarachchi, Vajisha U
Scogings, Chris
Susnjak, Teo
Mathrani, Anuradha
author_facet Wanniarachchi, Vajisha U
Scogings, Chris
Susnjak, Teo
Mathrani, Anuradha
author_sort Wanniarachchi, Vajisha U
collection PubMed
description This study investigates how female and male genders are positioned in fat stigmatising discourses that are being conducted over social media. Weight-based linguistic data corpus, extracted from three popular social media (SM) outlets, Twitter, YouTube and Reddit, was examined for fat stigmatising content. A mixed-method analysis comprising sentiment analysis, word co-occurrences and qualitative analysis, assisted our investigation of the corpus for body objectification themes and gender-based differences. Objectification theory provided the underlying framework to examine the experiential consequences of being fat across both genders. Five objectifying themes, namely, attractiveness, physical appearance, lifestyle choices, health and psychological well-being, emerged from the analysis. A deeper investigation into more facets of the social interaction data revealed overall positive and negative attitudes towards obesity, which informed on existing notions of gendered body objectification and weight/fat stigmatisation. Our findings have provided a holistic outlook on weight/fat stigmatising content that is posted online which can further inform policymakers in planning suitable props to facilitate more inclusive SM spaces. This study showcases how lexical analytics can be conducted by combining a variety of data mining methods to draw out insightful subject-related themes that add to the existing knowledge base; therefore, has both practical and theoretical implications.
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spelling pubmed-93868572022-08-19 Fat stigma and body objectification: A text analysis approach using social media content Wanniarachchi, Vajisha U Scogings, Chris Susnjak, Teo Mathrani, Anuradha Digit Health Original Research This study investigates how female and male genders are positioned in fat stigmatising discourses that are being conducted over social media. Weight-based linguistic data corpus, extracted from three popular social media (SM) outlets, Twitter, YouTube and Reddit, was examined for fat stigmatising content. A mixed-method analysis comprising sentiment analysis, word co-occurrences and qualitative analysis, assisted our investigation of the corpus for body objectification themes and gender-based differences. Objectification theory provided the underlying framework to examine the experiential consequences of being fat across both genders. Five objectifying themes, namely, attractiveness, physical appearance, lifestyle choices, health and psychological well-being, emerged from the analysis. A deeper investigation into more facets of the social interaction data revealed overall positive and negative attitudes towards obesity, which informed on existing notions of gendered body objectification and weight/fat stigmatisation. Our findings have provided a holistic outlook on weight/fat stigmatising content that is posted online which can further inform policymakers in planning suitable props to facilitate more inclusive SM spaces. This study showcases how lexical analytics can be conducted by combining a variety of data mining methods to draw out insightful subject-related themes that add to the existing knowledge base; therefore, has both practical and theoretical implications. SAGE Publications 2022-08-15 /pmc/articles/PMC9386857/ /pubmed/35990109 http://dx.doi.org/10.1177/20552076221117404 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Original Research
Wanniarachchi, Vajisha U
Scogings, Chris
Susnjak, Teo
Mathrani, Anuradha
Fat stigma and body objectification: A text analysis approach using social media content
title Fat stigma and body objectification: A text analysis approach using social media content
title_full Fat stigma and body objectification: A text analysis approach using social media content
title_fullStr Fat stigma and body objectification: A text analysis approach using social media content
title_full_unstemmed Fat stigma and body objectification: A text analysis approach using social media content
title_short Fat stigma and body objectification: A text analysis approach using social media content
title_sort fat stigma and body objectification: a text analysis approach using social media content
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9386857/
https://www.ncbi.nlm.nih.gov/pubmed/35990109
http://dx.doi.org/10.1177/20552076221117404
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