Abstract
China has embraced the social media domain to promote pro-Chinese narratives and stories in recent years. However, China has increasingly been accused of launching information operations using methods such as bot activity, puppet accounts and other forms of inauthentic activity to amplify pro-Chinese messaging. This paper provides a comprehensive network analysis characterization of the hashtag influence campaign China promoted against the US-hosted Summit on Democracy in December 2021, in addition to methods to identify different types of actors within this type of influence campaign.
This work was supported in part by the Knight Foundation and the Office of Naval Research grant Minerva-Multi-Level Models of Covert Online Information Campaigns (N00014-21-1-2765). Additional support was provided by the Center for Computational Analysis of Social and Organizational Systems (CASOS) at Carnegie Mellon University. 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 Knight Foundation, Office of Naval Research, or the U.S. Government.
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References
Beskow, D.M., Carley, K.M.: Bot-hunter: a tiered approach to detecting & characterizing automated activity on twitter. In: Conference Paper. SBP-BRiMS: International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation, vol. 3, p. 3 (2018)
Beskow, D.M., Carley, K.M.: Characterization and comparison of Russian and Chinese disinformation campaigns. In: Shu, K., Wang, S., Lee, D., Liu, H. (eds.) Disinformation, Misinformation, and Fake News in Social Media. LNSN, pp. 63–81. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-42699-6_4
DiResta, R., Goldstein, J.A.: China’s fake twitter accounts are tweeting into the void. Foreign Policy (2021)
Huang, Z.A., Wang, R.: Building a network to “tell china stories well’’: Chinese diplomatic communication strategies on twitter. Int. J. Commun. 13, 24 (2019)
Myers, S.L., Mozur, P., Kao, J.: How Bots and Fake Accounts Push China’s Vision of Winter Olympic Wonderland. ProPublica (2022)
Ng, L.H.X., Robertson, D.C., Carley, K.M.: Stabilizing a supervised bot detection algorithm: how much data is needed for consistent predictions? Online Soc. Networks Media“ 28, 100198 (2022)
Schafer, B.: China Fires Back at Biden with Conspiracy Theories About Maryland Lab. Foreign Policy (2021)
TwitterSafety: Disclosing state-linked information operations we’ve removed (2021). https://blog.twitter.com/en_us/topics/company/2021/disclosing-state-linked-information-operations-we-ve-removed
Uyheng, J., Carley, K.M.: Characterizing bot networks on twitter: an empirical analysis of contentious issues in the Asia-Pacific. In: Thomson, R., Bisgin, H., Dancy, C., Hyder, A. (eds.) SBP-BRiMS 2019. LNCS, vol. 11549, pp. 153–162. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-21741-9_16
Waltman, L., van Eck, N.J.: A smart local moving algorithm for large-scale modularity-based community detection. Eur. Phys. J. B 86(11), 1–14 (2013). https://doi.org/10.1140/epjb/e2013-40829-0
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Jacobs, C.S., Carley, K.M. (2022). #WhoDefinesDemocracy: Analysis on a 2021 Chinese Messaging Campaign. In: Thomson, R., Dancy, C., Pyke, A. (eds) Social, Cultural, and Behavioral Modeling. SBP-BRiMS 2022. Lecture Notes in Computer Science, vol 13558. Springer, Cham. https://doi.org/10.1007/978-3-031-17114-7_9
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