Characterizing Bot Networks on Twitter: An Empirical Analysis of Contentious Issues in the Asia-Pacific

  • Joshua UyhengEmail author
  • Kathleen M. Carley
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11549)


This paper empirically analyzes bot activity in contentious Twitter conversations using case studies from the Asia-Pacific. Bot activity is measured and characterized using a series of interoperable tools leveraging dynamic network analysis and machine learning. We apply this novel and flexible methodological framework to derive insights about information operations in three contexts: the senatorial elections in the Philippines, the presidential elections in Indonesia, and the relocation of a military base in Okinawa. Varying levels of bot prevalence and influence are identified across case studies. The presented findings demonstrate principles of social cyber-security in concrete settings and highlight conceptual and methodological issues to inform further development of analytic pipelines in studying online information operations.


Information operations Social cyber-security Asia-Pacific 



This work is supported in part by the Office of Naval Research under the Multidisciplinary University Research Initiatives (MURI) Program award number N000141712675 Near Real Time Assessment of Emergent Complex Systems of Confederates, BotHunter award number N000141812108, award number N00014182106 Group Polarization in Social Media: An Effective Network Approach to Communicative Reach and Disinformation, and award number N000141712605 Developing Novel Socio-computational Methodologies to Analyze Multimedia-based Cyber Propaganda Campaigns. This work is also supported by the center for Computational Analysis of Social and Organizational Systems (CASOS). The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the ONR or the U.S. government.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.CASOS, Institute for Software ResearchCarnegie Mellon UniversityPittsburghUSA

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