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Understanding Potential Cyber-Armies in Elections: A Study of Taiwan

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  • Ming-Hung Wang

    (Department of Information Engineering and Computer Science, Feng Chia University, Taichung 40724, Taiwan)

  • Nhut-Lam Nguyen

    (Department of Information Engineering and Computer Science, Feng Chia University, Taichung 40724, Taiwan)

  • Shih-chan Dai

    (Department of Political Science, University of Massachusetts Amherst, Amherst, MA 01003, USA)

  • Po-Wen Chi

    (Department of Computer Science and Information Engineering, National Taiwan Normal University, Taipei City 11677, Taiwan)

  • Chyi-Ren Dow

    (Department of Information Engineering and Computer Science, Feng Chia University, Taichung 40724, Taiwan)

Abstract

Currently, online social networks are essential platforms for political organizations to monitor public opinion, disseminate information, argue with the opposition, and even achieve spin control. However, once such purposeful/aggressive articles flood social sites, it would be more difficult for users to distinguish which messages to read or to trust. In this paper, we aim to address this issue by identifying potential “cyber-armies/professional users” during election campaigns on social platforms. We focus on human-operated accounts who try to influence public discussions, for instance, by publishing hundreds/thousands of comments to show their support or rejection of particular candidates. To achieve our objectives, we collected activity data over six months from a prominent Taiwan-based social forum before the 2018 national election and applied a series of statistical analyses to screen out potential targets. From the results, we successfully identified several accounts according to distinctive characteristics that corresponded to professional users. According to the findings, users and platforms could realize potential information manipulation and increase the transparency of the online society.

Suggested Citation

  • Ming-Hung Wang & Nhut-Lam Nguyen & Shih-chan Dai & Po-Wen Chi & Chyi-Ren Dow, 2020. "Understanding Potential Cyber-Armies in Elections: A Study of Taiwan," Sustainability, MDPI, vol. 12(6), pages 1-18, March.
  • Handle: RePEc:gam:jsusta:v:12:y:2020:i:6:p:2248-:d:332030
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    References listed on IDEAS

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    1. Oecd, 2001. "Understanding the Digital Divide," OECD Digital Economy Papers 49, OECD Publishing.
    2. Steinert-Threlkeld, Zachary C., 2017. "Spontaneous Collective Action: Peripheral Mobilization During the Arab Spring," American Political Science Review, Cambridge University Press, vol. 111(2), pages 379-403, May.
    3. 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.
    4. Taufiq Ahmad & Aima Alvi & Muhammad Ittefaq, 2019. "The Use of Social Media on Political Participation Among University Students: An Analysis of Survey Results From Rural Pakistan," SAGE Open, , vol. 9(3), pages 21582440198, July.
    5. Berinsky, Adam J., 2017. "Rumors and Health Care Reform: Experiments in Political Misinformation," British Journal of Political Science, Cambridge University Press, vol. 47(2), pages 241-262, April.
    6. Yianis Sarafidis, 2007. "What Have you Done for me Lately? Release of Information and Strategic Manipulation of Memories," Economic Journal, Royal Economic Society, vol. 117(518), pages 307-326, March.
    7. Xinxin Li & Lorin M. Hitt, 2008. "Self-Selection and Information Role of Online Product Reviews," Information Systems Research, INFORMS, vol. 19(4), pages 456-474, December.
    Full references (including those not matched with items on IDEAS)

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