Fear goes viral: the digital securitization of immigration in the 2024 elections

Abstract

Immigration was among the defining issues of the 2024 electoral cycle on both sides of the Atlantic. This study examines how the securitization framing of immigration in campaign discourse — its construction as an existential threat — relates to electoral mobilization, and whether the affordances of social-media platforms amplify that frame. It compares two dissimilar democratic contexts: the 2024 U.S. presidential election and the 2024 European Parliament elections. Combining framing theory and securitization theory, the study adopts a mixed-methods, most-different-systems design. It analyzes 155,827 news-influencer posts (Pew Research Center/Knight Initiative), video-level TikTok engagement data for 247 videos from Donald Trump and five European right-wing/populist leaders (via Exolyt), and official party manifestos, integrating quantitative content analysis, social-media analytics, and qualitative discourse analysis. The design is observational, and all quantitative analyses were performed in R. Securitization intensity is strongly associated with engagement (r = 0.73, p < 0.001), and high-intensity threat language attracts roughly 2.3× the engagement of moderate messaging. Cross-Atlantic convergence is pronounced for economic-threat (r = 0.84) and border-security (r = 0.91) frames. Within individual leader accounts, however, immigration/security content does not command an engagement premium (0.97×), indicating that platform uptake tracks affective and mobilizational formats as much as the securitizing frame itself. The findings support H1–H3. The reported relationships are correlational, not causal. Results suggest that algorithmic curation forms part of the securitizing apparatus by governing audience uptake, while cautioning that engagement is an ambiguous proxy conflating attention, approval, and outrage. The study contributes a systematic, quantitative extension of securitization analysis to the algorithmic environment of short-form video.