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Who Leads? Who Follows? Exploring Agenda Setting by Media, Social Bots and Public in the Discussion of the 2022 South Korean Presidential Election

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  • Menghan Zhang
  • Xue Qi
  • Xinyan Liu
  • Ke Zhang

Abstract

Social media not only changes the traditional communication environment but also brings new changes to agenda-setting. The main body of agenda-setting has shifted from the traditional media to the politicians, political parties and grassroots people. With the increasing use of social bots in public opinion manipulation and political election interference, whether they can participate in or influence agenda-setting has become an urgent concern. So far, there has been less literature focusing on engagement in agenda-setting for social bots. This paper studies the social media discussion content of the South Korean presidential election, determines the participation of social bots, and explores the connection between media agenda, bot agenda, and public agenda from the perspective of agenda setting. This study finds that while the main agendas of media, social bots, and the public are not the same, their agendas are relevant. In addition, the media agenda is not timely ahead of the bot agenda and the public agenda, and the time order only appears between the social bots and the public.

Suggested Citation

  • Menghan Zhang & Xue Qi & Xinyan Liu & Ke Zhang, 2024. "Who Leads? Who Follows? Exploring Agenda Setting by Media, Social Bots and Public in the Discussion of the 2022 South Korean Presidential Election," SAGE Open, , vol. 14(2), pages 21582440241, May.
    • Handle: RePEc:sae:sagope:v:14:y:2024:i:2:p:21582440241248891
    DOI: 10.1177/21582440241248891
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    References listed on IDEAS

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    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. Menghan Zhang & Xue Qi & Ze Chen & Jun Liu, 2022. "Social Bots’ Involvement in the COVID-19 Vaccine Discussions on Twitter," IJERPH, MDPI, vol. 19(3), pages 1-14, January.
    3. Steven Lehrer & Tian Xie & Tao Zeng, 2021. "Does High-Frequency Social Media Data Improve Forecasts of Low-Frequency Consumer Confidence Measures? [Regression Models with Mixed Sampling Frequencies]," Journal of Financial Econometrics, Oxford University Press, vol. 19(5), pages 910-933.
    4. McClosky, Herbert & Chong, Dennis, 1985. "Similarities and Differences Between Left-Wing and Right-Wing Radicals," British Journal of Political Science, Cambridge University Press, vol. 15(3), pages 329-363, July.
    5. Deva Woodly, 2008. "New competencies in democratic communication? Blogs, agenda setting and political participation," Public Choice, Springer, vol. 134(1), pages 109-123, January.
    6. 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.
    7. 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.
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