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The far right is increasingly relying on visual and less extreme online communication, for instance by using memes, to strategically mainstream their ideology. The use of humor in particular renders their communication more relatable to a mainstream audience. However, little is known about the actual impacts of the different content characteristics they employ to become more appealing, in particular on less moderated platforms that function as safe online spaces for extremist ideology and contents. To fill this gap, we conducted a manual quantitative content analysis of 1,200 memes distributed within German-language far-right Telegram channels in 2020 and 2021, concentrating on humor and several content-related factors to analyze their impact on meme reach. The results demonstrate that memes with extreme far-right narratives and memes with humor received fewer views than others, but that memes with both far-right narratives and humor had a significantly increased reach. The findings highlight the mainstreaming potential of humor, particularly when used to mask extreme content that would otherwise be less appealing.

Crafted as an open communication platform characterized by high anonymity and minimal moderation, Telegram has garnered increasing popularity among activists operating within repressive political contexts, as well as among political extremists and conspiracy theorists. While Telegram offers valuable data access to research non-institutionalized activism, scholars studying the latter on Telegram face unique theoretical and methodological challenges in systematically defining, selecting, sampling, and classifying relevant actors and content. This literature review addresses these issues by considering a wide range of recent research. In particular, it discusses the methodological challenges of sampling and classifying heterogeneous groups of (often non-institutionalized) actors. Drawing on social movement research, we first identify challenges specific to the characteristics of non-institutionalized actors and how they become interlaced with Telegram’s platform infrastructure and requirements. We then discuss strategies from previous Telegram research for the identification and sampling of a study population through multistage sampling procedures and the classification of actors. Finally, we derive challenges and potential strategies for future research and discuss ethical challenges.