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Promoting and countering misinformation during Australia’s 2019–2020 bushfires: a case study of polarisation
During Australia’s unprecedented bushfires in 2019–2020, misinformation blaming arson surfaced on Twitter using #ArsonEmergency. The extent to which bots and trolls were responsible for disseminating and amplifying this misinformation has received media scrutiny and academic research. Here, we study...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Vienna
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243896/ https://www.ncbi.nlm.nih.gov/pubmed/35789892 http://dx.doi.org/10.1007/s13278-022-00892-x |
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author | Weber, Derek Falzon, Lucia Mitchell, Lewis Nasim, Mehwish |
author_facet | Weber, Derek Falzon, Lucia Mitchell, Lewis Nasim, Mehwish |
author_sort | Weber, Derek |
collection | PubMed |
description | During Australia’s unprecedented bushfires in 2019–2020, misinformation blaming arson surfaced on Twitter using #ArsonEmergency. The extent to which bots and trolls were responsible for disseminating and amplifying this misinformation has received media scrutiny and academic research. Here, we study Twitter communities spreading this misinformation during the newsworthy event, and investigate the role of online communities using a natural experiment approach—before and after reporting of bots promoting the hashtag was broadcast by the mainstream media. Few bots were found, but the most bot-like accounts were social bots, which present as genuine humans, and trolling behaviour was evident. Further, we distilled meaningful quantitative differences between two polarised communities in the Twitter discussion, resulting in the following insights. First, Supporters of the arson narrative promoted misinformation by engaging others directly with replies and mentions using hashtags and links to external sources. In response, Opposers retweeted fact-based articles and official information. Second, Supporters were embedded throughout their interaction networks, but Opposers obtained high centrality more efficiently despite their peripheral positions. By the last phase, Opposers and unaffiliated accounts appeared to coordinate, potentially reaching a broader audience. Finally, the introduction of the bot report changed the discussion dynamic: Opposers only responded immediately, while Supporters countered strongly for days, but new unaffiliated accounts drawn into the discussion shifted the dominant narrative from arson misinformation to factual and official information. This foiled Supporters’ efforts, highlighting the value of exposing misinformation. We speculate that the communication strategies observed here could inform counter-strategies in other misinformation-related discussions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13278-022-00892-x. |
format | Online Article Text |
id | pubmed-9243896 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Vienna |
record_format | MEDLINE/PubMed |
spelling | pubmed-92438962022-06-30 Promoting and countering misinformation during Australia’s 2019–2020 bushfires: a case study of polarisation Weber, Derek Falzon, Lucia Mitchell, Lewis Nasim, Mehwish Soc Netw Anal Min Original Article During Australia’s unprecedented bushfires in 2019–2020, misinformation blaming arson surfaced on Twitter using #ArsonEmergency. The extent to which bots and trolls were responsible for disseminating and amplifying this misinformation has received media scrutiny and academic research. Here, we study Twitter communities spreading this misinformation during the newsworthy event, and investigate the role of online communities using a natural experiment approach—before and after reporting of bots promoting the hashtag was broadcast by the mainstream media. Few bots were found, but the most bot-like accounts were social bots, which present as genuine humans, and trolling behaviour was evident. Further, we distilled meaningful quantitative differences between two polarised communities in the Twitter discussion, resulting in the following insights. First, Supporters of the arson narrative promoted misinformation by engaging others directly with replies and mentions using hashtags and links to external sources. In response, Opposers retweeted fact-based articles and official information. Second, Supporters were embedded throughout their interaction networks, but Opposers obtained high centrality more efficiently despite their peripheral positions. By the last phase, Opposers and unaffiliated accounts appeared to coordinate, potentially reaching a broader audience. Finally, the introduction of the bot report changed the discussion dynamic: Opposers only responded immediately, while Supporters countered strongly for days, but new unaffiliated accounts drawn into the discussion shifted the dominant narrative from arson misinformation to factual and official information. This foiled Supporters’ efforts, highlighting the value of exposing misinformation. We speculate that the communication strategies observed here could inform counter-strategies in other misinformation-related discussions. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13278-022-00892-x. Springer Vienna 2022-06-24 2022 /pmc/articles/PMC9243896/ /pubmed/35789892 http://dx.doi.org/10.1007/s13278-022-00892-x Text en © Crown 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Weber, Derek Falzon, Lucia Mitchell, Lewis Nasim, Mehwish Promoting and countering misinformation during Australia’s 2019–2020 bushfires: a case study of polarisation |
title | Promoting and countering misinformation during Australia’s 2019–2020 bushfires: a case study of polarisation |
title_full | Promoting and countering misinformation during Australia’s 2019–2020 bushfires: a case study of polarisation |
title_fullStr | Promoting and countering misinformation during Australia’s 2019–2020 bushfires: a case study of polarisation |
title_full_unstemmed | Promoting and countering misinformation during Australia’s 2019–2020 bushfires: a case study of polarisation |
title_short | Promoting and countering misinformation during Australia’s 2019–2020 bushfires: a case study of polarisation |
title_sort | promoting and countering misinformation during australia’s 2019–2020 bushfires: a case study of polarisation |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243896/ https://www.ncbi.nlm.nih.gov/pubmed/35789892 http://dx.doi.org/10.1007/s13278-022-00892-x |
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