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Bots and online hate during the COVID-19 pandemic: case studies in the United States and the Philippines

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  • Joshua Uyheng

    (Carnegie Mellon University)

  • Kathleen M. Carley

    (Carnegie Mellon University)

Abstract

Online hate speech represents a serious problem exacerbated by the ongoing COVID-19 pandemic. Although often anchored in real-world social divisions, hate speech in cyberspace may also be fueled inorganically by inauthentic actors like social bots. This work presents and employs a methodological pipeline for assessing the links between hate speech and bot-driven activity through the lens of social cybersecurity. Using a combination of machine learning and network science tools, we empirically characterize Twitter conversations about the pandemic in the United States and the Philippines. Our integrated analysis reveals idiosyncratic relationships between bots and hate speech across datasets, highlighting different network dynamics of racially charged toxicity in the US and political conflicts in the Philippines. Most crucially, we discover that bot activity is linked to higher hate in both countries, especially in communities which are denser and more isolated from others. We discuss several insights for probing issues of online hate speech and coordinated disinformation, especially through a global approach to computational social science.

Suggested Citation

  • Joshua Uyheng & Kathleen M. Carley, 2020. "Bots and online hate during the COVID-19 pandemic: case studies in the United States and the Philippines," Journal of Computational Social Science, Springer, vol. 3(2), pages 445-468, November.
    • Handle: RePEc:spr:jcsosc:v:3:y:2020:i:2:d:10.1007_s42001-020-00087-4
    DOI: 10.1007/s42001-020-00087-4
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    1. Angelo Antoci & Alexia Delfino & Fabio Paglieri & Fabrizio Panebianco & Fabio Sabatini, 2016. "Civility vs. Incivility in Online Social Interactions: An Evolutionary Approach," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-17, November.
    2. Susan Morgan, 2018. "Fake news, disinformation, manipulation and online tactics to undermine democracy," Journal of Cyber Policy, Taylor & Francis Journals, vol. 3(1), pages 39-43, January.
    3. Christopher A. Bail & Lisa P. Argyle & Taylor W. Brown & John P. Bumpus & Haohan Chen & M. B. Fallin Hunzaker & Jaemin Lee & Marcus Mann & Friedolin Merhout & Alexander Volfovsky, 2018. "Exposure to opposing views on social media can increase political polarization," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(37), pages 9216-9221, September.
    4. Massimo Stella & Emilio Ferrara & Manlio De Domenico, 2018. "Bots increase exposure to negative and inflammatory content in online social systems," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(49), pages 12435-12440, December.
    5. N. F. Johnson & R. Leahy & N. Johnson Restrepo & N. Velasquez & M. Zheng & P. Manrique & P. Devkota & S. Wuchty, 2019. "Hidden resilience and adaptive dynamics of the global online hate ecology," Nature, Nature, vol. 573(7773), pages 261-265, September.
    6. Chengcheng Shao & Giovanni Luca Ciampaglia & Onur Varol & Kai-Cheng Yang & Alessandro Flammini & Filippo Menczer, 2018. "The spread of low-credibility content by social bots," Nature Communications, Nature, vol. 9(1), pages 1-9, December.
    7. Bjarke Mønsted & Piotr Sapieżyński & Emilio Ferrara & Sune Lehmann, 2017. "Evidence of complex contagion of information in social media: An experiment using Twitter bots," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-12, September.
    8. Joseph Henrich & Steven J. Heine & Ara Norenzayan, 2010. "Most people are not WEIRD," Nature, Nature, vol. 466(7302), pages 29-29, July.
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    Cited by:

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    3. Kai-Cheng Yang & Emilio Ferrara & Filippo Menczer, 2022. "Botometer 101: social bot practicum for computational social scientists," Journal of Computational Social Science, Springer, vol. 5(2), pages 1511-1528, November.
    4. Anna Ruelens, 2022. "Analyzing user-generated content using natural language processing: a case study of public satisfaction with healthcare systems," Journal of Computational Social Science, Springer, vol. 5(1), pages 731-749, May.
    5. Zixuan Weng & Aijun Lin, 2022. "Public Opinion Manipulation on Social Media: Social Network Analysis of Twitter Bots during the COVID-19 Pandemic," IJERPH, MDPI, vol. 19(24), pages 1-17, December.
    6. Wentao Xu & Kazutoshi Sasahara, 2022. "Characterizing the roles of bots on Twitter during the COVID-19 infodemic," Journal of Computational Social Science, Springer, vol. 5(1), pages 591-609, May.
    7. Francesca Bolla Tripodi, 2022. "ReOpen demands as public health threat: a sociotechnical framework for understanding the stickiness of misinformation," Computational and Mathematical Organization Theory, Springer, vol. 28(4), pages 321-334, December.
    8. Vicente Javier Clemente-Suárez & Eduardo Navarro-Jiménez & Libertad Moreno-Luna & María Concepción Saavedra-Serrano & Manuel Jimenez & Juan Antonio Simón & Jose Francisco Tornero-Aguilera, 2021. "The Impact of the COVID-19 Pandemic on Social, Health, and Economy," Sustainability, MDPI, vol. 13(11), pages 1-25, June.
    9. Yaming Zhang & Wenjie Song & Jiang Shao & Majed Abbas & Jiaqi Zhang & Yaya H. Koura & Yanyuan Su, 2023. "Social Bots’ Role in the COVID-19 Pandemic Discussion on Twitter," IJERPH, MDPI, vol. 20(4), pages 1-21, February.
    10. J. Franceschi & L. Pareschi & M. Zanella, 2022. "From agent-based models to the macroscopic description of fake-news spread: the role of competence in data-driven applications," Partial Differential Equations and Applications, Springer, vol. 3(6), pages 1-26, December.

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