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Active, aggressive, but to little avail: characterizing bot activity during the 2020 Singaporean elections
Digital disinformation presents a challenging problem for democracies worldwide, especially in times of crisis like the COVID-19 pandemic. In countries like Singapore, legislative efforts to quell fake news constitute relatively new and understudied contexts for understanding local information opera...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8095478/ https://www.ncbi.nlm.nih.gov/pubmed/33967594 http://dx.doi.org/10.1007/s10588-021-09332-1 |
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author | Uyheng, Joshua Ng, Lynnette Hui Xian Carley, Kathleen M. |
author_facet | Uyheng, Joshua Ng, Lynnette Hui Xian Carley, Kathleen M. |
author_sort | Uyheng, Joshua |
collection | PubMed |
description | Digital disinformation presents a challenging problem for democracies worldwide, especially in times of crisis like the COVID-19 pandemic. In countries like Singapore, legislative efforts to quell fake news constitute relatively new and understudied contexts for understanding local information operations. This paper presents a social cybersecurity analysis of the 2020 Singaporean elections, which took place at the height of the pandemic and after the recent passage of an anti-fake news law. Harnessing a dataset of 240,000 tweets about the elections, we found that 26.99% of participating accounts were likely to be bots, responsible for a larger proportion of bot tweets than the election in 2015. Textual analysis further showed that the detected bots used simpler and more abusive second-person language, as well as hashtags related to COVID-19 and voter activity—pointing to aggressive tactics potentially fuelling online hostility and questioning the legitimacy of the polls. Finally, bots were associated with larger, less dense, and less echo chamber-like communities, suggesting efforts to participate in larger, mainstream conversations. However, despite their distinct narrative and network maneuvers, bots generally did not hold significant influence throughout the social network. Hence, although intersecting concerns of political conflict during a global pandemic may promptly raise the possibility of online interference, we quantify both the efforts and limits of bot-fueled disinformation in the 2020 Singaporean elections. We conclude with several implications for digital disinformation in times of crisis, in the Asia-Pacific and beyond. |
format | Online Article Text |
id | pubmed-8095478 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-80954782021-05-05 Active, aggressive, but to little avail: characterizing bot activity during the 2020 Singaporean elections Uyheng, Joshua Ng, Lynnette Hui Xian Carley, Kathleen M. Comput Math Organ Theory S.I. : SBP-BRiMS2020 Digital disinformation presents a challenging problem for democracies worldwide, especially in times of crisis like the COVID-19 pandemic. In countries like Singapore, legislative efforts to quell fake news constitute relatively new and understudied contexts for understanding local information operations. This paper presents a social cybersecurity analysis of the 2020 Singaporean elections, which took place at the height of the pandemic and after the recent passage of an anti-fake news law. Harnessing a dataset of 240,000 tweets about the elections, we found that 26.99% of participating accounts were likely to be bots, responsible for a larger proportion of bot tweets than the election in 2015. Textual analysis further showed that the detected bots used simpler and more abusive second-person language, as well as hashtags related to COVID-19 and voter activity—pointing to aggressive tactics potentially fuelling online hostility and questioning the legitimacy of the polls. Finally, bots were associated with larger, less dense, and less echo chamber-like communities, suggesting efforts to participate in larger, mainstream conversations. However, despite their distinct narrative and network maneuvers, bots generally did not hold significant influence throughout the social network. Hence, although intersecting concerns of political conflict during a global pandemic may promptly raise the possibility of online interference, we quantify both the efforts and limits of bot-fueled disinformation in the 2020 Singaporean elections. We conclude with several implications for digital disinformation in times of crisis, in the Asia-Pacific and beyond. Springer US 2021-05-04 2021 /pmc/articles/PMC8095478/ /pubmed/33967594 http://dx.doi.org/10.1007/s10588-021-09332-1 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, 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 | S.I. : SBP-BRiMS2020 Uyheng, Joshua Ng, Lynnette Hui Xian Carley, Kathleen M. Active, aggressive, but to little avail: characterizing bot activity during the 2020 Singaporean elections |
title | Active, aggressive, but to little avail: characterizing bot activity during the 2020 Singaporean elections |
title_full | Active, aggressive, but to little avail: characterizing bot activity during the 2020 Singaporean elections |
title_fullStr | Active, aggressive, but to little avail: characterizing bot activity during the 2020 Singaporean elections |
title_full_unstemmed | Active, aggressive, but to little avail: characterizing bot activity during the 2020 Singaporean elections |
title_short | Active, aggressive, but to little avail: characterizing bot activity during the 2020 Singaporean elections |
title_sort | active, aggressive, but to little avail: characterizing bot activity during the 2020 singaporean elections |
topic | S.I. : SBP-BRiMS2020 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8095478/ https://www.ncbi.nlm.nih.gov/pubmed/33967594 http://dx.doi.org/10.1007/s10588-021-09332-1 |
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