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May 17, 2026
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Abstract

Migration has become one of the most contested issues in contemporary European public debate, where news coverage often frames migrants through the language of border control, legality, and public order. Such securitized representations may contribute to keeping migrants at a symbolic distance from audiences, presenting them less as socially embedded individuals and more as categories to be regulated or governed. While previous research has examined media representations of migration and online hate speech separately, less is known about how migration-related news content is associated with the hostile reactions that can emerge among social media audiences exposed to this content.
This study addresses this gap by analyzing migration-related Instagram posts published by eight major Italian news organizations between January 2025 and March 2026, together with the comments they generated. A corpus of 368 news posts and 76,998 user comments was analyzed by combining topic modeling of news posts with automated emotion detection and hate speech classification of user comments to examine how securitized thematic environments are associated with hostile audience responses. The results show that audience reactions were marked by a strong prevalence of negative emotions, with anger emerging as the dominant response across the corpus. This affective profile became more polarized in relation to news posts that framed migration through legal-institutional conflict, return procedures, border enforcement, and NGO-related controversies. In these securitized contexts, audience responses were more strongly concentrated around anger and disgust, and this emotional concentration was accompanied by higher levels of hate speech.

Keywords

Migration Hate Speech Securitization Media Framing Instagram Emoption Detection Topic Modeling Computational Social Science

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How to Cite
Ludovico, N., Rizzoli, V., Yilmaz, A. D., Lucarini, A., Cocco, V. M., & Vezzali, L. (2026). Securitized migration news and hostile audience reactions on Instagram: a computational analysis of Italian news posts and user comments. Journal of E-Learning and Knowledge Society, 22(1). https://doi.org/10.20368/1971-8829/1136366

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