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Bots increase exposure to negative and inflammatory content in online social systems

Author

Listed:
  • Massimo Stella

    (Center for Information and Communication Technology, Fondazione Bruno Kessler, 38123 Trento, Italy)

  • Emilio Ferrara

    (USC Information Sciences Institute, University of Southern California, Marina del Rey, CA 90292)

  • Manlio De Domenico

    (Center for Information and Communication Technology, Fondazione Bruno Kessler, 38123 Trento, Italy)

Abstract

Societies are complex systems, which tend to polarize into subgroups of individuals with dramatically opposite perspectives. This phenomenon is reflected—and often amplified—in online social networks, where, however, humans are no longer the only players and coexist alongside with social bots—that is, software-controlled accounts. Analyzing large-scale social data collected during the Catalan referendum for independence on October 1, 2017, consisting of nearly 4 millions Twitter posts generated by almost 1 million users, we identify the two polarized groups of Independentists and Constitutionalists and quantify the structural and emotional roles played by social bots. We show that bots act from peripheral areas of the social system to target influential humans of both groups, bombarding Independentists with violent contents, increasing their exposure to negative and inflammatory narratives, and exacerbating social conflict online. Our findings stress the importance of developing countermeasures to unmask these forms of automated social manipulation.

Suggested Citation

  • 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.
    • Handle: RePEc:nas:journl:v:115:y:2018:p:12435-12440
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    Cited by:

    1. Menghan Zhang & Ze Chen & Xue Qi & Jun Liu, 2022. "Could Social Bots’ Sentiment Engagement Shape Humans’ Sentiment on COVID-19 Vaccine Discussion on Twitter?," Sustainability, MDPI, vol. 14(9), pages 1-16, May.
    2. Eminente, Clara & Artime, Oriol & De Domenico, Manlio, 2022. "Interplay between exogenous triggers and endogenous behavioral changes in contagion processes on social networks," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    3. Quintino Francesco Lotito & Davide Zanella & Paolo Casari, 2021. "Realistic Aspects of Simulation Models for Fake News Epidemics over Social Networks," Future Internet, MDPI, vol. 13(3), pages 1-20, March.
    4. Kelton Minor & Esteban Moro & Nick Obradovich, 2023. "Adverse weather amplifies social media activity," Papers 2302.08456, arXiv.org.
    5. Malik, Nishtha & Kar, Arpan Kumar & Tripathi, Shalini Nath & Gupta, Shivam, 2023. "Exploring the impact of fairness of social bots on user experience," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
    6. 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.
    7. Wen Shi & Diyi Liu & Jing Yang & Jing Zhang & Sanmei Wen & Jing Su, 2020. "Social Bots’ Sentiment Engagement in Health Emergencies: A Topic-Based Analysis of the COVID-19 Pandemic Discussions on Twitter," IJERPH, MDPI, vol. 17(22), pages 1-18, November.
    8. Raffaele Mattera & Michelangelo Misuraca & Maria Spano & Germana Scepi, 2023. "Mixed frequency composite indicators for measuring public sentiment in the EU," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2357-2382, June.
    9. Yaniv Abir & Caroline B. Marvin & Camilla Geen & Maya Leshkowitz & Ran R. Hassin & Daphna Shohamy, 2022. "An energizing role for motivation in information-seeking during the early phase of the COVID-19 pandemic," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    10. Riccardo Gallotti & Francesco Valle & Nicola Castaldo & Pierluigi Sacco & Manlio De Domenico, 2020. "Assessing the risks of ‘infodemics’ in response to COVID-19 epidemics," Nature Human Behaviour, Nature, vol. 4(12), pages 1285-1293, December.
    11. Cheng, Chun & Luo, Yun & Yu, Changbin, 2020. "Dynamic mechanism of social bots interfering with public opinion in network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    12. Saumya Bhadani & Shun Yamaya & Alessandro Flammini & Filippo Menczer & Giovanni Luca Ciampaglia & Brendan Nyhan, 2022. "Political audience diversity and news reliability in algorithmic ranking," Nature Human Behaviour, Nature, vol. 6(4), pages 495-505, April.
    13. Min, Yong & Zhou, Yuying & Liu, Yuhang & Zhang, Jian & Xuan, Qi & Jin, Xiaogang & Cai, He, 2021. "The role of degree correlation in shaping filter bubbles in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 584(C).
    14. 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.
    15. 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.
    16. Hyehyun Hong & Hyun Jee Oh, 2020. "Utilizing Bots for Sustainable News Business: Understanding Users’ Perspectives of News Bots in the Age of Social Media," Sustainability, MDPI, vol. 12(16), pages 1-16, August.
    17. Ross Schuchard & Andrew Crooks & Anthony Stefanidis & Arie Croitoru, 2019. "Bots fired: examining social bot evidence in online mass shooting conversations," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-12, December.
    18. José M. Oller & Albert Satorra & Adolf Tobeña, 2019. "Unveiling pathways for the fissure among secessionists and unionists in Catalonia: identities, family language, and media influence," Palgrave Communications, Palgrave Macmillan, vol. 5(1), pages 1-13, December.
    19. Ciaglia, Floriana & Stella, Massimo & Kennington, Casey, 2023. "Investigating preferential acquisition and attachment in early word learning through cognitive, visual and latent multiplex lexical networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 612(C).

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