APSIPA Transactions on Signal and Information Processing > Vol 11 > Issue 2

A Network-Based Approach to QAnon User Dynamics and Topic Diversity During the COVID-19 Infodemic

Wentao Xu, Graduate School of Informatics, Nagoya University, Japan, myrainbowandsky@gmail.com , Kazutoshi Sasahara, School of Environment and Society, Tokyo Institute of Technology, Japan, sasahara.k.aa@m.titech.ac.jp
 
Suggested Citation
Wentao Xu and Kazutoshi Sasahara (2022), "A Network-Based Approach to QAnon User Dynamics and Topic Diversity During the COVID-19 Infodemic", APSIPA Transactions on Signal and Information Processing: Vol. 11: No. 2, e17. http://dx.doi.org/10.1561/116.00000055

Publication Date: 14 Jun 2022
© 2022 W. Xu and K. Sasahara
 
Subjects
 
Keywords
COVID-19infodemicnetworksQAnon conspiracy theorytopic diversityuser dynamics
 

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In this article:
Introduction 
Data and Methods 
Results 
Discussion 
References 

Abstract

QAnon is an umbrella conspiracy theory that encompasses a wide spectrum of people. The COVID-19 pandemic has helped raise the QAnon conspiracy theory to a wide-spreading movement, especially in the US. Here, we study users’ dynamics on Twitter related to the QAnon movement (i.e., pro-/anti-QAnon and less-leaning users) in the context of the COVID-19 infodemic and the topics involved using a simple network-based approach. We found that pro- and anti-leaning users show different population dynamics and that late less-leaning users were mostly anti-QAnon. These trends might have been affected by Twitter’s suspension strategies. We also found that QAnon clusters include many bot users. Furthermore, our results suggest that QAnon continues to evolve amid the infodemic and does not limit itself to its original idea but instead extends its reach to create a much larger umbrella conspiracy theory. The network-based approach in this study is important for nowcasting the evolution of the QAnon movement.

DOI:10.1561/116.00000055

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APSIPA Transactions on Signal and Information Processing Special Issue - Multi-Disciplinary Dis/Misinformation Analysis and Countermeasures: Articles Overview
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