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Stigmatizing Attitudes Across Cybersuicides and Offline Suicides: Content Analysis of Sina Weibo

BACKGROUND: The new reality of cybersuicide raises challenges to ideologies about the traditional form of suicide that does not involve the internet (offline suicide), which may lead to changes in audience’s attitudes. However, knowledge on whether stigmatizing attitudes differ between cybersuicides...

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Detalles Bibliográficos
Autores principales: Li, Ang, Jiao, Dongdong, Zhu, Tingshao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9034432/
https://www.ncbi.nlm.nih.gov/pubmed/35394437
http://dx.doi.org/10.2196/36489
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author Li, Ang
Jiao, Dongdong
Zhu, Tingshao
author_facet Li, Ang
Jiao, Dongdong
Zhu, Tingshao
author_sort Li, Ang
collection PubMed
description BACKGROUND: The new reality of cybersuicide raises challenges to ideologies about the traditional form of suicide that does not involve the internet (offline suicide), which may lead to changes in audience’s attitudes. However, knowledge on whether stigmatizing attitudes differ between cybersuicides and offline suicides remains limited. OBJECTIVE: This study aims to consider livestreamed suicide as a typical representative of cybersuicide and use social media data (Sina Weibo) to investigate the differences in stigmatizing attitudes across cybersuicides and offline suicides in terms of attitude types and linguistic characteristics. METHODS: A total of 4393 cybersuicide-related and 2843 offline suicide-related Weibo posts were collected and analyzed. First, human coders were recruited and trained to perform a content analysis on the collected posts to determine whether each of them reflected stigma. Second, a text analysis tool was used to automatically extract a number of psycholinguistic features from each post. Subsequently, based on the selected features, a series of classification models were constructed for different purposes: differentiating the general stigma of cybersuicide from that of offline suicide and differentiating the negative stereotypes of cybersuicide from that of offline suicide. RESULTS: In terms of attitude types, cybersuicide was observed to carry more stigma than offline suicide (χ(2)(1)=179.8; P<.001). Between cybersuicides and offline suicides, there were significant differences in the proportion of posts associated with five different negative stereotypes, including stupid and shallow (χ(2)(1)=28.9; P<.001), false representation (χ(2)(1)=144.4; P<.001), weak and pathetic (χ(2)(1)=20.4; P<.001), glorified and normalized (χ(2)(1)=177.6; P<.001), and immoral (χ(2)(1)=11.8; P=.001). Similar results were also found for different genders and regions. In terms of linguistic characteristics, the F-measure values of the classification models ranged from 0.81 to 0.85. CONCLUSIONS: The way people perceive cybersuicide differs from how they perceive offline suicide. The results of this study have implications for reducing the stigma against suicide.
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spelling pubmed-90344322022-04-24 Stigmatizing Attitudes Across Cybersuicides and Offline Suicides: Content Analysis of Sina Weibo Li, Ang Jiao, Dongdong Zhu, Tingshao J Med Internet Res Original Paper BACKGROUND: The new reality of cybersuicide raises challenges to ideologies about the traditional form of suicide that does not involve the internet (offline suicide), which may lead to changes in audience’s attitudes. However, knowledge on whether stigmatizing attitudes differ between cybersuicides and offline suicides remains limited. OBJECTIVE: This study aims to consider livestreamed suicide as a typical representative of cybersuicide and use social media data (Sina Weibo) to investigate the differences in stigmatizing attitudes across cybersuicides and offline suicides in terms of attitude types and linguistic characteristics. METHODS: A total of 4393 cybersuicide-related and 2843 offline suicide-related Weibo posts were collected and analyzed. First, human coders were recruited and trained to perform a content analysis on the collected posts to determine whether each of them reflected stigma. Second, a text analysis tool was used to automatically extract a number of psycholinguistic features from each post. Subsequently, based on the selected features, a series of classification models were constructed for different purposes: differentiating the general stigma of cybersuicide from that of offline suicide and differentiating the negative stereotypes of cybersuicide from that of offline suicide. RESULTS: In terms of attitude types, cybersuicide was observed to carry more stigma than offline suicide (χ(2)(1)=179.8; P<.001). Between cybersuicides and offline suicides, there were significant differences in the proportion of posts associated with five different negative stereotypes, including stupid and shallow (χ(2)(1)=28.9; P<.001), false representation (χ(2)(1)=144.4; P<.001), weak and pathetic (χ(2)(1)=20.4; P<.001), glorified and normalized (χ(2)(1)=177.6; P<.001), and immoral (χ(2)(1)=11.8; P=.001). Similar results were also found for different genders and regions. In terms of linguistic characteristics, the F-measure values of the classification models ranged from 0.81 to 0.85. CONCLUSIONS: The way people perceive cybersuicide differs from how they perceive offline suicide. The results of this study have implications for reducing the stigma against suicide. JMIR Publications 2022-04-08 /pmc/articles/PMC9034432/ /pubmed/35394437 http://dx.doi.org/10.2196/36489 Text en ©Ang Li, Dongdong Jiao, Tingshao Zhu. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 08.04.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), 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 https://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Li, Ang
Jiao, Dongdong
Zhu, Tingshao
Stigmatizing Attitudes Across Cybersuicides and Offline Suicides: Content Analysis of Sina Weibo
title Stigmatizing Attitudes Across Cybersuicides and Offline Suicides: Content Analysis of Sina Weibo
title_full Stigmatizing Attitudes Across Cybersuicides and Offline Suicides: Content Analysis of Sina Weibo
title_fullStr Stigmatizing Attitudes Across Cybersuicides and Offline Suicides: Content Analysis of Sina Weibo
title_full_unstemmed Stigmatizing Attitudes Across Cybersuicides and Offline Suicides: Content Analysis of Sina Weibo
title_short Stigmatizing Attitudes Across Cybersuicides and Offline Suicides: Content Analysis of Sina Weibo
title_sort stigmatizing attitudes across cybersuicides and offline suicides: content analysis of sina weibo
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9034432/
https://www.ncbi.nlm.nih.gov/pubmed/35394437
http://dx.doi.org/10.2196/36489
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