Abstract
Coordinated disinformation campaigns are used to influence social media users, potentially leading to offline violence. In this study, we introduce a general methodology to uncover coordinated messaging through an analysis of user posts on Parler. The proposed Coordinating Narratives Framework constructs a user-to-user coordination graph, which is induced by a user-to-text graph and a text-to-text similarity graph. The text-to-text graph is constructed based on the textual similarity of Parler and Twitter posts. We study three influential groups of users in the 6 January 2020 Capitol riots and detect networks of coordinated user clusters that post similar textual content in support of disinformation narratives related to the U.S. 2020 elections. We further extend our methodology to Twitter tweets to identify authors that share the same disinformation messaging as the aforementioned Parler user groups.
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Code for parsing Parler HTML is available at: https://github.com/...
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Acknowledgements
The research for this paper was supported in part by the Knight Foundation and the Office of Naval Research Grant (N000141812106) and an Omar N. Bradley Fellowship, and by the center for Informed Democracy and Social-cybersecurity (IDeaS) and the center for Computational Analysis of Social and Organizational Systems (CASOS) at Carnegie Mellon University. The views and conclusions 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 US Government.
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Ng, L.H.X., Cruickshank, I.J. & Carley, K.M. Coordinating Narratives Framework for cross-platform analysis in the 2021 US Capitol riots. Comput Math Organ Theory 29, 470–486 (2023). https://doi.org/10.1007/s10588-022-09371-2
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DOI: https://doi.org/10.1007/s10588-022-09371-2