Social Media Algorithms and Securitization Practices in Everyday Life on Social Media

Abstract

This article examines how social media algorithms operate as infrastructures of everyday securitization shaping the digital lives of our life. Departing from state-centric and event-driven security frameworks, it conceptualizes algorithms as mechanisms of security governance that continuously curate visibility, risk, and normality within platform environments. Through processes of recommendation, ranking, and engagement optimization, algorithms delineate what is rendered threatening, risky, or in need of intervention, embedding securitization within routine digital practices. Drawing on critical security studies and scholarship on algorithmic governance, the article argues that social media platforms function as sites of everyday securitization where security logics are enacted without explicit declarations of threat. We are governed not merely as users but as a population classified through algorithmic distinctions between safe, risky, and vulnerable subjects. These classifications shape subjectivities by aligning participation, affect, and visibility with norms of digital security and behavioral compliance. The article further advances an affective account of securitization, showing how fear, anxiety, and outrage are privileged as engagement drivers, normalizing a persistent yet low-intensity sense of insecurity. It concludes with a normative critique, highlighting the depoliticizing effects of algorithmic securitization and calling for a repoliticization of platform-based security governance