Knowledge Graphs of the QAnon Twitter Network

Clay Adams, Malvina Bozhidarova, James Chen, Andrew Gao, Zhengtong Liu, J. Hunter Priniski, Junyuan Lin, Rishi Sonthalia, Andrea L. Bertozzi, P. Jeffrey Brantingham

Abstract: Using Knowledge Graphs to understand noisy naturalistic data has gained significant prominence in recent years. In this paper, we apply Knowledge Graphs to a new dataset of tweets of an ideologically far-right Twitter network by sourcing tweet histories of users who discussed QAnon in the summer of 2018 [1]. We further develop a new method that arms topic models with relational information from Knowledge Graphs and apply the new technique to study this dataset. Our analysis shows that users do not form a monolithic belief or social network, but rather comprise many smaller interlinking communities which discuss unique key political events (e.g., the January 6 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">th</sup> Capitol riots).