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Exploring the Functioning of Online Self-Organizations during Public Health Emergencies: Patterns and Mechanism

With the increasing use of social media, online self-organized relief has become a crucial aspect of crisis management during public health emergencies, leading to the emergence of online self-organizations. This study employed the BERT model to classify the replies of Weibo users and used K-means c...

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Autores principales: Chen, Jinghao, Liu, Qianxi, Liu, Xiaoyan, Wang, Youfeng, Nie, Huizi, Xie, Xiankun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10002262/
https://www.ncbi.nlm.nih.gov/pubmed/36901022
http://dx.doi.org/10.3390/ijerph20054012
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author Chen, Jinghao
Liu, Qianxi
Liu, Xiaoyan
Wang, Youfeng
Nie, Huizi
Xie, Xiankun
author_facet Chen, Jinghao
Liu, Qianxi
Liu, Xiaoyan
Wang, Youfeng
Nie, Huizi
Xie, Xiankun
author_sort Chen, Jinghao
collection PubMed
description With the increasing use of social media, online self-organized relief has become a crucial aspect of crisis management during public health emergencies, leading to the emergence of online self-organizations. This study employed the BERT model to classify the replies of Weibo users and used K-means clustering to summarize the patterns of self-organized groups and communities. We then combined the findings from pattern discovery and documents from online relief networks to analyze the core components and mechanisms of online self-organizations. Our findings indicate the following: (1) The composition of online self-organized groups follows Pareto’s law. (2) Online self-organized communities are mainly composed of sparse and small groups with loose connections, and bot accounts can automatically identify those in need and provide them with helpful information and resources. (3) The core components of the mechanism of online self-organized rescue groups include the initial gathering of groups, the formation of key groups, the generation of collective action, and the establishment of organizational norms. This study suggests that social media can establish an authentication mechanism for online self-organizations, and that authorities should encourage online interactive live streams about public health issues. However, it is important to note that self-organizations are not a panacea for all issues during public health emergencies.
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spelling pubmed-100022622023-03-11 Exploring the Functioning of Online Self-Organizations during Public Health Emergencies: Patterns and Mechanism Chen, Jinghao Liu, Qianxi Liu, Xiaoyan Wang, Youfeng Nie, Huizi Xie, Xiankun Int J Environ Res Public Health Article With the increasing use of social media, online self-organized relief has become a crucial aspect of crisis management during public health emergencies, leading to the emergence of online self-organizations. This study employed the BERT model to classify the replies of Weibo users and used K-means clustering to summarize the patterns of self-organized groups and communities. We then combined the findings from pattern discovery and documents from online relief networks to analyze the core components and mechanisms of online self-organizations. Our findings indicate the following: (1) The composition of online self-organized groups follows Pareto’s law. (2) Online self-organized communities are mainly composed of sparse and small groups with loose connections, and bot accounts can automatically identify those in need and provide them with helpful information and resources. (3) The core components of the mechanism of online self-organized rescue groups include the initial gathering of groups, the formation of key groups, the generation of collective action, and the establishment of organizational norms. This study suggests that social media can establish an authentication mechanism for online self-organizations, and that authorities should encourage online interactive live streams about public health issues. However, it is important to note that self-organizations are not a panacea for all issues during public health emergencies. MDPI 2023-02-23 /pmc/articles/PMC10002262/ /pubmed/36901022 http://dx.doi.org/10.3390/ijerph20054012 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chen, Jinghao
Liu, Qianxi
Liu, Xiaoyan
Wang, Youfeng
Nie, Huizi
Xie, Xiankun
Exploring the Functioning of Online Self-Organizations during Public Health Emergencies: Patterns and Mechanism
title Exploring the Functioning of Online Self-Organizations during Public Health Emergencies: Patterns and Mechanism
title_full Exploring the Functioning of Online Self-Organizations during Public Health Emergencies: Patterns and Mechanism
title_fullStr Exploring the Functioning of Online Self-Organizations during Public Health Emergencies: Patterns and Mechanism
title_full_unstemmed Exploring the Functioning of Online Self-Organizations during Public Health Emergencies: Patterns and Mechanism
title_short Exploring the Functioning of Online Self-Organizations during Public Health Emergencies: Patterns and Mechanism
title_sort exploring the functioning of online self-organizations during public health emergencies: patterns and mechanism
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10002262/
https://www.ncbi.nlm.nih.gov/pubmed/36901022
http://dx.doi.org/10.3390/ijerph20054012
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