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#Antivaccination on Instagram: A Computational Analysis of Hashtag Activism through Photos and Public Responses
A dramatic increase has been registered in the number of social media posts in photo form as well as in hashtag activism. Hashtags, which manifest thoughts and feelings clearly and concisely, originated on Twitter, where the length of a post is limited; their use, however, has expanded into other so...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7589874/ https://www.ncbi.nlm.nih.gov/pubmed/33080782 http://dx.doi.org/10.3390/ijerph17207550 |
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author | Kim, Yunhwan Song, Donghwi Lee, Yeon Ju |
author_facet | Kim, Yunhwan Song, Donghwi Lee, Yeon Ju |
author_sort | Kim, Yunhwan |
collection | PubMed |
description | A dramatic increase has been registered in the number of social media posts in photo form as well as in hashtag activism. Hashtags, which manifest thoughts and feelings clearly and concisely, originated on Twitter, where the length of a post is limited; their use, however, has expanded into other social media services, including Instagram. Hashtags, which make it easy to find and express support for posts of interest, have been widely used for online activism, although they have been criticized for fostering confirmation bias. Moreover, hashtag activism in photo form has been relatively understudied. This research analyzed Instagram photos with antivaccination hashtags as an example of hashtag activism through photos. In addition, we examined how the photo features were related to public response, which was manifested via engagement and comment sentiment. The results suggest that the photos which were categorized into “text” took the largest share. It was also found that the major way of claiming was to imprint key messages that persuade people not to vaccinate with remarks from professionals on photos and provide a source of supporting information in the post text with hashtags of antivaccine intention. Various photo features showed associations with engagement and comment sentiment, but the directions of correlation were usually the opposite: these results suggest that engagement and comment sentiment are separate domains that reveal different public responses. |
format | Online Article Text |
id | pubmed-7589874 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75898742020-10-29 #Antivaccination on Instagram: A Computational Analysis of Hashtag Activism through Photos and Public Responses Kim, Yunhwan Song, Donghwi Lee, Yeon Ju Int J Environ Res Public Health Article A dramatic increase has been registered in the number of social media posts in photo form as well as in hashtag activism. Hashtags, which manifest thoughts and feelings clearly and concisely, originated on Twitter, where the length of a post is limited; their use, however, has expanded into other social media services, including Instagram. Hashtags, which make it easy to find and express support for posts of interest, have been widely used for online activism, although they have been criticized for fostering confirmation bias. Moreover, hashtag activism in photo form has been relatively understudied. This research analyzed Instagram photos with antivaccination hashtags as an example of hashtag activism through photos. In addition, we examined how the photo features were related to public response, which was manifested via engagement and comment sentiment. The results suggest that the photos which were categorized into “text” took the largest share. It was also found that the major way of claiming was to imprint key messages that persuade people not to vaccinate with remarks from professionals on photos and provide a source of supporting information in the post text with hashtags of antivaccine intention. Various photo features showed associations with engagement and comment sentiment, but the directions of correlation were usually the opposite: these results suggest that engagement and comment sentiment are separate domains that reveal different public responses. MDPI 2020-10-17 2020-10 /pmc/articles/PMC7589874/ /pubmed/33080782 http://dx.doi.org/10.3390/ijerph17207550 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Kim, Yunhwan Song, Donghwi Lee, Yeon Ju #Antivaccination on Instagram: A Computational Analysis of Hashtag Activism through Photos and Public Responses |
title | #Antivaccination on Instagram: A Computational Analysis of Hashtag Activism through Photos and Public Responses |
title_full | #Antivaccination on Instagram: A Computational Analysis of Hashtag Activism through Photos and Public Responses |
title_fullStr | #Antivaccination on Instagram: A Computational Analysis of Hashtag Activism through Photos and Public Responses |
title_full_unstemmed | #Antivaccination on Instagram: A Computational Analysis of Hashtag Activism through Photos and Public Responses |
title_short | #Antivaccination on Instagram: A Computational Analysis of Hashtag Activism through Photos and Public Responses |
title_sort | #antivaccination on instagram: a computational analysis of hashtag activism through photos and public responses |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7589874/ https://www.ncbi.nlm.nih.gov/pubmed/33080782 http://dx.doi.org/10.3390/ijerph17207550 |
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