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Use of bot and content flags to limit the spread of misinformation among social networks: a behavior and attitude survey
The COVID-19 infodemic is driven partially by Twitter bots. Flagging bot accounts and the misinformation they share could provide one strategy for preventing the spread of false information online. This article reports on an experiment (N = 299) conducted with participants in the USA to see whether...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Vienna
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7954364/ https://www.ncbi.nlm.nih.gov/pubmed/33747252 http://dx.doi.org/10.1007/s13278-021-00739-x |
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author | Lanius, Candice Weber, Ryan MacKenzie, William I. |
author_facet | Lanius, Candice Weber, Ryan MacKenzie, William I. |
author_sort | Lanius, Candice |
collection | PubMed |
description | The COVID-19 infodemic is driven partially by Twitter bots. Flagging bot accounts and the misinformation they share could provide one strategy for preventing the spread of false information online. This article reports on an experiment (N = 299) conducted with participants in the USA to see whether flagging tweets as coming from bot accounts and as containing misinformation can lower participants’ self-reported engagement and attitudes about the tweets. This experiment also showed participants tweets that aligned with their previously held beliefs to determine how flags affect their overall opinions. Results showed that flagging tweets lowered participants’ attitudes about them, though this effect was less pronounced in participants who frequently used social media or consumed more news, especially from Facebook or Fox News. Some participants also changed their opinions after seeing the flagged tweets. The results suggest that social media companies can flag suspicious or inaccurate content as a way to fight misinformation. Flagging could be built into future automated fact-checking systems and other misinformation abatement strategies of the social network analysis and mining community. |
format | Online Article Text |
id | pubmed-7954364 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Vienna |
record_format | MEDLINE/PubMed |
spelling | pubmed-79543642021-03-15 Use of bot and content flags to limit the spread of misinformation among social networks: a behavior and attitude survey Lanius, Candice Weber, Ryan MacKenzie, William I. Soc Netw Anal Min Original Article The COVID-19 infodemic is driven partially by Twitter bots. Flagging bot accounts and the misinformation they share could provide one strategy for preventing the spread of false information online. This article reports on an experiment (N = 299) conducted with participants in the USA to see whether flagging tweets as coming from bot accounts and as containing misinformation can lower participants’ self-reported engagement and attitudes about the tweets. This experiment also showed participants tweets that aligned with their previously held beliefs to determine how flags affect their overall opinions. Results showed that flagging tweets lowered participants’ attitudes about them, though this effect was less pronounced in participants who frequently used social media or consumed more news, especially from Facebook or Fox News. Some participants also changed their opinions after seeing the flagged tweets. The results suggest that social media companies can flag suspicious or inaccurate content as a way to fight misinformation. Flagging could be built into future automated fact-checking systems and other misinformation abatement strategies of the social network analysis and mining community. Springer Vienna 2021-03-12 2021 /pmc/articles/PMC7954364/ /pubmed/33747252 http://dx.doi.org/10.1007/s13278-021-00739-x Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH, AT part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Article Lanius, Candice Weber, Ryan MacKenzie, William I. Use of bot and content flags to limit the spread of misinformation among social networks: a behavior and attitude survey |
title | Use of bot and content flags to limit the spread of misinformation among social networks: a behavior and attitude survey |
title_full | Use of bot and content flags to limit the spread of misinformation among social networks: a behavior and attitude survey |
title_fullStr | Use of bot and content flags to limit the spread of misinformation among social networks: a behavior and attitude survey |
title_full_unstemmed | Use of bot and content flags to limit the spread of misinformation among social networks: a behavior and attitude survey |
title_short | Use of bot and content flags to limit the spread of misinformation among social networks: a behavior and attitude survey |
title_sort | use of bot and content flags to limit the spread of misinformation among social networks: a behavior and attitude survey |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7954364/ https://www.ncbi.nlm.nih.gov/pubmed/33747252 http://dx.doi.org/10.1007/s13278-021-00739-x |
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