Nangle, B. M., & d’Haenens, L. (2026). Affective–discursive ecologies of the far right: Multimodal softening, mobilisation and algorithmic proximity on Instagram. New Media & Society. https://doi.org/10.1177/14614448261428632
Summary
This article examines how far-right actors on Instagram use positive affect, humour, and memetic content to normalise extremist worldviews. Rather than framing radicalisation as a matter of overt hostility, the authors argue that far-right Instagram operates as an “affective–discursive ecology” in which ideology, emotion, and platform logics are mutually constitutive. Drawing on algorithmic ethnography and multimodal discourse analysis of 2,603 Reels featuring far-right adjacent themes, the study shows how “multimodal softening” through humour and memes facilitates mainstreaming, while “algorithmic proximity” produces visibility and circulation that support mobilisation. The paper sits at the intersection of mainstreaming research, memetic and affective communication studies, and critical platform studies.
Key Contributions
- Introduces the concept of the affective–discursive ecology to theorise far-right communication on Instagram.
- Bridges literatures on mainstreaming, memetic communication, and affective publics with platform and algorithm studies.
- Provides a large-scale multimodal empirical analysis of far-right Reels — an under-studied format.
- Demonstrates a combined methodology of algorithmic ethnography and multimodal discourse analysis for studying extremism on visual platforms.
Methods
- Algorithmic ethnography of Instagram, tracing how far-right adjacent content circulates and is recommended.
- Multimodal discourse analysis attending to audiovisual, textual, and affective dimensions of Reels.
- Analysis of a dataset of 2,603 Reels featuring far-right adjacent themes.
Findings
- Far-right content relies on positive affect and humour rather than overt hostility to soften extremist messaging.
- Memetic and multimodal forms serve as vehicles for the normalisation and mainstreaming of far-right ideology.
- Platform algorithmic logics generate proximity between mainstream and far-right adjacent content, supporting mobilisation.
Connections
This paper’s emphasis on humour, memes, and affective softening resonates with work on the aesthetics and everyday styling of far-right online content such as Askanius2026-de and Grusauskaite2026-po, and its attention to algorithmic recommendation and visibility connects to platform-focused analyses like Rothut2026-or and Rothut2026-wt. Its account of mainstreaming through emotionally resonant content also relates to broader discussions of how platforms mediate extremism in Marwick2025-ov and Marwick2025-vx.