The Production of Anti-Islamic Discourse as a Rage Bait Strategy on Digital Platforms

Özet

This study, which interrogates how content related to Islam and Muslims is produced
on X accounts of global media organizations within the context of rage bait strategies
and digital hate speech, is based on a content analysis method. Posts obtained from
the accounts of Daily Mail, Der Spiegel, The Sun, and BBC Breaking News between
14 February 2026 and 5 April 2026 were examined through purposive sampling. The
data were analyzed using engagement metrics such as likes, comments, reposts,
quotes, and views, and were further subjected to discursive framing and thematic
coding. The findings indicate that Islam and Muslim identity are frequently
represented within negative frames centered on themes of security, violence,
terrorism, and crisis. It was found that rage bait strategies increase engagement
production through emotional triggering, provocative language, and in-group/out-
group distinctions, which, in combination with algorithmic visibility mechanisms,
amplify the circulation of hate speech. In addition, although the content does not
always generate high engagement directly, it carries Islamophobic potential in terms
of its discursive patterns. As a result, the study demonstrates that the production of
digital hate speech and Islamophobia is not solely ideological but also a structural
process linked to platform economies and algorithmic incentives. In this context, rage
bait is considered a complementary analytical category for explaining content
production. The findings suggest that visibility regimes based on emotional
engagement on digital platforms contribute to the normalization of hate speech and
generate significant regulatory needs in terms of media policy. By addressing the relationship between algorithmic visibility and the emotional economy in the context
of Islamophobia, the study opens a theoretical and empirical field of discussion in
the literature.