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

Published online by Cambridge University Press:  28 April 2026

Sahar Rasoulikolamaki*
Affiliation:
Department of English Language, Faculty of Languages and Linguistics, Universiti Malaya, Malaysia
Noor Aqsa Nabila Mat Isa
Affiliation:
Department of English Language, Faculty of Languages and Linguistics, Universiti Malaya, Malaysia
Alena Zhdanava
Affiliation:
Rabdan Academy, UAE
John Hardy
Affiliation:
Rabdan Academy, UAE
*
Corresponding author: Sahar Rasoulikolamaki; Email: sahar@um.edu.my
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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)

Information

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2026. Published by Cambridge University Press.
Figure 0

Table 1. Stance markers in QAnon+ anti-immigration comments.

Figure 1

Table 2. Emoji–text convergence in QAnon+ anti-immigration comments.

Figure 2

Table 3. Dialogic affiliation categories in QAnon+ anti-immigration emoji-only comments.