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Neutral bots probe political bias on social media

Author

Listed:
  • Wen Chen

    (Indiana University)

  • Diogo Pacheco

    (Indiana University
    University of Exeter)

  • Kai-Cheng Yang

    (Indiana University)

  • Filippo Menczer

    (Indiana University)

Abstract

Social media platforms attempting to curb abuse and misinformation have been accused of political bias. We deploy neutral social bots who start following different news sources on Twitter, and track them to probe distinct biases emerging from platform mechanisms versus user interactions. We find no strong or consistent evidence of political bias in the news feed. Despite this, the news and information to which U.S. Twitter users are exposed depend strongly on the political leaning of their early connections. The interactions of conservative accounts are skewed toward the right, whereas liberal accounts are exposed to moderate content shifting their experience toward the political center. Partisan accounts, especially conservative ones, tend to receive more followers and follow more automated accounts. Conservative accounts also find themselves in denser communities and are exposed to more low-credibility content.

Suggested Citation

  • Wen Chen & Diogo Pacheco & Kai-Cheng Yang & Filippo Menczer, 2021. "Neutral bots probe political bias on social media," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-25738-6
    DOI: 10.1038/s41467-021-25738-6
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    Cited by:

    1. 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.
    2. Chuhan Wu & Fangzhao Wu & Tao Qi & Wei-Qiang Zhang & Xing Xie & Yongfeng Huang, 2022. "Removing AI’s sentiment manipulation of personalized news delivery," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-9, December.

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