非表示:
キーワード:
Computer Science, Computers and Society, cs.CY,cs.SI
要旨:
QAnon is a far-right conspiracy theory that became popular and mainstream
over the past few years. Worryingly, the QAnon conspiracy theory has
implications in the real world, with supporters of the theory participating in
real-world violent acts like the US capitol attack in 2021. At the same time,
the QAnon theory started evolving into a global phenomenon by attracting
followers across the globe and, in particular, in Europe. Therefore, it is
imperative to understand how the QAnon theory became a worldwide phenomenon and
how this dissemination has been happening in the online space. This paper
performs a large-scale data analysis of QAnon through Telegram by collecting
4.5M messages posted in 161 QAnon groups/channels. Using Google's Perspective
API, we analyze the toxicity of QAnon content across languages and over time.
Also, using a BERT-based topic modeling approach, we analyze the QAnon
discourse across multiple languages. Among other things, we find that the
German language is prevalent in QAnon groups/channels on Telegram, even
overshadowing English after 2020. Also, we find that content posted in German
and Portuguese tends to be more toxic compared to English. Our topic modeling
indicates that QAnon supporters discuss various topics of interest within
far-right movements, including world politics, conspiracy theories, COVID-19,
and the anti-vaccination movement. Taken all together, we perform the first
multilingual study on QAnon through Telegram and paint a nuanced overview of
the globalization of the QAnon theory.
