Computational Analysis of Bot Activity in the Asia-Pacific: A Comparative Study of Four National Elections

Authors

  • Joshua Uyheng CASOS Center, Institute for Software Research, Carnegie Mellon University
  • Kathleen M. Carley CASOS Center, Institute for Software Research, Carnegie Mellon University

Keywords:

Social network analysis; communities identification; expertise and authority discovery, Credibility of online content, Subjectivity in textual data; sentiment analysis; polarity/opinion identification and extraction, linguistic analyses of social media behavior, Centrality/influence of social media publications and authors

Abstract

Bot-driven electoral disinformation represents a major threat to democracies worldwide. Extant scholarship, however, tends to concentrate around Western contexts. This paper undertakes a comparative computational analysis of bot activity during four recent elections in the Asia-Pacific. Through a systematic, multi-level comparison of bot activity, we contribute novel insights about shared and distinct computational features of the disinformation landscapes within a significant yet understudied geopolitical region. Across case studies in Indonesia, the Philippines, Singapore, and Taiwan, we find non-negligible levels of bot activity: bots engage in higher levels of tweet production; interact with humans especially through mentions; tend to occupy denser and more isolated communities; use simpler and abusive language; and share partisan, irrelevant, or conspiratorial content. We conclude with implications for deepening and utilizing the analysis presented here as well as future directions for further cross-national work.

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Published

2021-05-22

How to Cite

Uyheng, J., & Carley, K. M. (2021). Computational Analysis of Bot Activity in the Asia-Pacific: A Comparative Study of Four National Elections. Proceedings of the International AAAI Conference on Web and Social Media, 15(1), 727-738. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/18098