QAnon is a far-right conspiracy theory that became popular and mainstreamover the past few years. Worryingly, the QAnon conspiracy theory hasimplications in the real world, with supporters of the theory participating inreal-world violent acts like the US capitol attack in 2021. At the same time,the QAnon theory started evolving into a global phenomenon by attractingfollowers across the globe and, in particular, in Europe. Therefore, it isimperative to understand how the QAnon theory became a worldwide phenomenon andhow this dissemination has been happening in the online space. This paperperforms a large-scale data analysis of QAnon through Telegram by collecting4.5M messages posted in 161 QAnon groups/channels. Using Google's PerspectiveAPI, we analyze the toxicity of QAnon content across languages and over time.Also, using a BERT-based topic modeling approach, we analyze the QAnondiscourse across multiple languages. Among other things, we find that theGerman language is prevalent in QAnon groups/channels on Telegram, evenovershadowing English after 2020. Also, we find that content posted in Germanand Portuguese tends to be more toxic compared to English. Our topic modelingindicates that QAnon supporters discuss various topics of interest withinfar-right movements, including world politics, conspiracy theories, COVID-19,and the anti-vaccination movement. Taken all together, we perform the firstmultilingual study on QAnon through Telegram and paint a nuanced overview ofthe globalization of the QAnon theory.<br
