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Pro-Anorexia and Anti-Pro-Anorexia Videos on YouTube: Sentiment Analysis of User Responses
BACKGROUND: Pro-anorexia communities exist online and encourage harmful weight loss and weight control practices, often through emotional content that enforces social ties within these communities. User-generated responses to videos that directly oppose pro-anorexia communities have not yet been res...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications Inc.
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4704949/ https://www.ncbi.nlm.nih.gov/pubmed/26563678 http://dx.doi.org/10.2196/jmir.5007 |
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author | Oksanen, Atte Garcia, David Sirola, Anu Näsi, Matti Kaakinen, Markus Keipi, Teo Räsänen, Pekka |
author_facet | Oksanen, Atte Garcia, David Sirola, Anu Näsi, Matti Kaakinen, Markus Keipi, Teo Räsänen, Pekka |
author_sort | Oksanen, Atte |
collection | PubMed |
description | BACKGROUND: Pro-anorexia communities exist online and encourage harmful weight loss and weight control practices, often through emotional content that enforces social ties within these communities. User-generated responses to videos that directly oppose pro-anorexia communities have not yet been researched in depth. OBJECTIVE: The aim was to study emotional reactions to pro-anorexia and anti-pro-anorexia online content on YouTube using sentiment analysis. METHODS: Using the 50 most popular YouTube pro-anorexia and anti-pro-anorexia user channels as a starting point, we gathered data on users, their videos, and their commentators. A total of 395 anorexia videos and 12,161 comments were analyzed using positive and negative sentiments and ratings submitted by the viewers of the videos. The emotional information was automatically extracted with an automatic sentiment detection tool whose reliability was tested with human coders. Ordinary least squares regression models were used to estimate the strength of sentiments. The models controlled for the number of video views and comments, number of months the video had been on YouTube, duration of the video, uploader’s activity as a video commentator, and uploader’s physical location by country. RESULTS: The 395 videos had more than 6 million views and comments by almost 8000 users. Anti-pro-anorexia video comments expressed more positive sentiments on a scale of 1 to 5 (adjusted prediction [AP] 2.15, 95% CI 2.11-2.19) than did those of pro-anorexia videos (AP 2.02, 95% CI 1.98-2.06). Anti-pro-anorexia videos also received more likes (AP 181.02, 95% CI 155.19-206.85) than pro-anorexia videos (AP 31.22, 95% CI 31.22-37.81). Negative sentiments and video dislikes were equally distributed in responses to both pro-anorexia and anti-pro-anorexia videos. CONCLUSIONS: Despite pro-anorexia content being widespread on YouTube, videos promoting help for anorexia and opposing the pro-anorexia community were more popular, gaining more positive feedback and comments than pro-anorexia videos. Thus, the anti-pro-anorexia content provided a user-generated counterforce against pro-anorexia content on YouTube. Professionals working with young people should be aware of the social media dynamics and versatility of user-generated eating disorder content online. |
format | Online Article Text |
id | pubmed-4704949 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | JMIR Publications Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-47049492016-01-12 Pro-Anorexia and Anti-Pro-Anorexia Videos on YouTube: Sentiment Analysis of User Responses Oksanen, Atte Garcia, David Sirola, Anu Näsi, Matti Kaakinen, Markus Keipi, Teo Räsänen, Pekka J Med Internet Res Original Paper BACKGROUND: Pro-anorexia communities exist online and encourage harmful weight loss and weight control practices, often through emotional content that enforces social ties within these communities. User-generated responses to videos that directly oppose pro-anorexia communities have not yet been researched in depth. OBJECTIVE: The aim was to study emotional reactions to pro-anorexia and anti-pro-anorexia online content on YouTube using sentiment analysis. METHODS: Using the 50 most popular YouTube pro-anorexia and anti-pro-anorexia user channels as a starting point, we gathered data on users, their videos, and their commentators. A total of 395 anorexia videos and 12,161 comments were analyzed using positive and negative sentiments and ratings submitted by the viewers of the videos. The emotional information was automatically extracted with an automatic sentiment detection tool whose reliability was tested with human coders. Ordinary least squares regression models were used to estimate the strength of sentiments. The models controlled for the number of video views and comments, number of months the video had been on YouTube, duration of the video, uploader’s activity as a video commentator, and uploader’s physical location by country. RESULTS: The 395 videos had more than 6 million views and comments by almost 8000 users. Anti-pro-anorexia video comments expressed more positive sentiments on a scale of 1 to 5 (adjusted prediction [AP] 2.15, 95% CI 2.11-2.19) than did those of pro-anorexia videos (AP 2.02, 95% CI 1.98-2.06). Anti-pro-anorexia videos also received more likes (AP 181.02, 95% CI 155.19-206.85) than pro-anorexia videos (AP 31.22, 95% CI 31.22-37.81). Negative sentiments and video dislikes were equally distributed in responses to both pro-anorexia and anti-pro-anorexia videos. CONCLUSIONS: Despite pro-anorexia content being widespread on YouTube, videos promoting help for anorexia and opposing the pro-anorexia community were more popular, gaining more positive feedback and comments than pro-anorexia videos. Thus, the anti-pro-anorexia content provided a user-generated counterforce against pro-anorexia content on YouTube. Professionals working with young people should be aware of the social media dynamics and versatility of user-generated eating disorder content online. JMIR Publications Inc. 2015-11-12 /pmc/articles/PMC4704949/ /pubmed/26563678 http://dx.doi.org/10.2196/jmir.5007 Text en ©Atte Oksanen, David Garcia, Anu Sirola, Matti Näsi, Markus Kaakinen, Teo Keipi, Pekka Räsänen. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 12.11.2015. https://creativecommons.org/licenses/by/2.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/ (https://creativecommons.org/licenses/by/2.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Oksanen, Atte Garcia, David Sirola, Anu Näsi, Matti Kaakinen, Markus Keipi, Teo Räsänen, Pekka Pro-Anorexia and Anti-Pro-Anorexia Videos on YouTube: Sentiment Analysis of User Responses |
title | Pro-Anorexia and Anti-Pro-Anorexia Videos on YouTube: Sentiment Analysis of User Responses |
title_full | Pro-Anorexia and Anti-Pro-Anorexia Videos on YouTube: Sentiment Analysis of User Responses |
title_fullStr | Pro-Anorexia and Anti-Pro-Anorexia Videos on YouTube: Sentiment Analysis of User Responses |
title_full_unstemmed | Pro-Anorexia and Anti-Pro-Anorexia Videos on YouTube: Sentiment Analysis of User Responses |
title_short | Pro-Anorexia and Anti-Pro-Anorexia Videos on YouTube: Sentiment Analysis of User Responses |
title_sort | pro-anorexia and anti-pro-anorexia videos on youtube: sentiment analysis of user responses |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4704949/ https://www.ncbi.nlm.nih.gov/pubmed/26563678 http://dx.doi.org/10.2196/jmir.5007 |
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