Abstract
While substantial research has focused on social bot classification, less computational effort has focused on repeatable bot characterization. Binary classification into “bot” or “not bot” is just the first step in social cybersecurity workflows. Characterizing the malicious actors is the next step. To that end, this paper will characterize data associated with state sponsored manipulation by Russia and the People’s Republic of China. The data studied here was associated with information manipulation by state actors, the accounts were suspended by Twitter and subsequently all associated data was released to the public. Of the multiple data sets that Twitter released, we will focus on the data associated with the Russian Internet Research Agency and the People’s Republic of China. The goal of this paper is to compare and contrast these two important data sets while simultaneously developing repeatable workflows to characterize information operations for social cybersecurity.
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Acknowledgements
This work was supported in part by the Office of Naval Research (ONR) Award N00014182106 and Award N000141812108, and the Center for Computational Analysis of Social and Organization 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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Beskow, D.M., Carley, K.M. (2020). 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. Lecture Notes in Social Networks. Springer, Cham. https://doi.org/10.1007/978-3-030-42699-6_4
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