Multimodal stance-taking and ideological alignment in online far-right anti-immigration discourse

Abstract With rising political polarisation, far-right digital spaces have become fertile ground for amplifying xenophobic discourse. Adopting a critical multimodal analytic approach to stance analysis, we examined anti-immigration posts and comments related to the US context in the QAnon+ Telegram channel from January 2021 to October 2022 to show that radicalisation in this context is not merely a matter of extreme opinions, but of the performative multimodal enactment of stance that drives ideological alignment. The anti-immigration discourse is dominated by attitude markers and boosters, while hedging and self-mention are scarce, reflecting a tendency towards affective intensity and ideological closure over deliberation or reflexivity. Emojis, as paralinguistic resources, co-perform stance by amplifying shared outrage and mobilising group alignment. The overall argument is that hate in radical digital publics is enacted through patterned multimodal and performative processes, explaining the mechanisms that make such spaces resilient to rational counter-argument and potent for collective extremism. (Anti-immigration, far-right, multimodal critical discourse analysis, group alignment, performativity, QAnon, stance-taking)