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Social Bots’ Role in the COVID-19 Pandemic Discussion on Twitter

Social bots have already infiltrated social media platforms, such as Twitter, Facebook, and so on. Exploring the role of social bots in discussions of the COVID-19 pandemic, as well as comparing the behavioral differences between social bots and humans, is an important foundation for studying public...

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Detalles Bibliográficos
Autores principales: Zhang, Yaming, Song, Wenjie, Shao, Jiang, Abbas, Majed, Zhang, Jiaqi, Koura, Yaya H., Su, Yanyuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9967279/
https://www.ncbi.nlm.nih.gov/pubmed/36833983
http://dx.doi.org/10.3390/ijerph20043284
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author Zhang, Yaming
Song, Wenjie
Shao, Jiang
Abbas, Majed
Zhang, Jiaqi
Koura, Yaya H.
Su, Yanyuan
author_facet Zhang, Yaming
Song, Wenjie
Shao, Jiang
Abbas, Majed
Zhang, Jiaqi
Koura, Yaya H.
Su, Yanyuan
author_sort Zhang, Yaming
collection PubMed
description Social bots have already infiltrated social media platforms, such as Twitter, Facebook, and so on. Exploring the role of social bots in discussions of the COVID-19 pandemic, as well as comparing the behavioral differences between social bots and humans, is an important foundation for studying public health opinion dissemination. We collected data on Twitter and used Botometer to classify users into social bots and humans. Machine learning methods were used to analyze the characteristics of topic semantics, sentiment attributes, dissemination intentions, and interaction patterns of humans and social bots. The results show that 22% of these accounts were social bots, while 78% were humans, and there are significant differences in the behavioral characteristics between them. Social bots are more concerned with the topics of public health news than humans are with individual health and daily lives. More than 85% of bots’ tweets are liked, and they have a large number of followers and friends, which means they have influence on internet users’ perceptions about disease transmission and public health. In addition, social bots, located mainly in Europe and America countries, create an “authoritative” image by posting a lot of news, which in turn gains more attention and has a significant effect on humans. The findings contribute to understanding the behavioral patterns of new technologies such as social bots and their role in the dissemination of public health information.
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spelling pubmed-99672792023-02-26 Social Bots’ Role in the COVID-19 Pandemic Discussion on Twitter Zhang, Yaming Song, Wenjie Shao, Jiang Abbas, Majed Zhang, Jiaqi Koura, Yaya H. Su, Yanyuan Int J Environ Res Public Health Article Social bots have already infiltrated social media platforms, such as Twitter, Facebook, and so on. Exploring the role of social bots in discussions of the COVID-19 pandemic, as well as comparing the behavioral differences between social bots and humans, is an important foundation for studying public health opinion dissemination. We collected data on Twitter and used Botometer to classify users into social bots and humans. Machine learning methods were used to analyze the characteristics of topic semantics, sentiment attributes, dissemination intentions, and interaction patterns of humans and social bots. The results show that 22% of these accounts were social bots, while 78% were humans, and there are significant differences in the behavioral characteristics between them. Social bots are more concerned with the topics of public health news than humans are with individual health and daily lives. More than 85% of bots’ tweets are liked, and they have a large number of followers and friends, which means they have influence on internet users’ perceptions about disease transmission and public health. In addition, social bots, located mainly in Europe and America countries, create an “authoritative” image by posting a lot of news, which in turn gains more attention and has a significant effect on humans. The findings contribute to understanding the behavioral patterns of new technologies such as social bots and their role in the dissemination of public health information. MDPI 2023-02-13 /pmc/articles/PMC9967279/ /pubmed/36833983 http://dx.doi.org/10.3390/ijerph20043284 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
Zhang, Yaming
Song, Wenjie
Shao, Jiang
Abbas, Majed
Zhang, Jiaqi
Koura, Yaya H.
Su, Yanyuan
Social Bots’ Role in the COVID-19 Pandemic Discussion on Twitter
title Social Bots’ Role in the COVID-19 Pandemic Discussion on Twitter
title_full Social Bots’ Role in the COVID-19 Pandemic Discussion on Twitter
title_fullStr Social Bots’ Role in the COVID-19 Pandemic Discussion on Twitter
title_full_unstemmed Social Bots’ Role in the COVID-19 Pandemic Discussion on Twitter
title_short Social Bots’ Role in the COVID-19 Pandemic Discussion on Twitter
title_sort social bots’ role in the covid-19 pandemic discussion on twitter
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9967279/
https://www.ncbi.nlm.nih.gov/pubmed/36833983
http://dx.doi.org/10.3390/ijerph20043284
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