Public Opinion, Propaganda and Politics of Algorithmic Influence

This paper examines how public opinion, propaganda, and the politics of algorithmic influence intersect in today’s digital communication environment. As social media platforms become dominant channels for political information, algorithmic systems increasingly shape what people see, believe, and share. The study explores how algorithm-driven content curation affects political visibility, reinforces selective exposure, and contributes to the formation—or distortion—of public opinion. It also analyses how modern propaganda adapts to these algorithmic environments. Instead of viewing propaganda only as manipulation, the paper considers it as part of broader political communication strategies, while acknowledging its potential for ideological shaping, emotional targeting, and narrative amplification. Special attention is given to how political actors, digital platforms, and citizens interact within algorithmic systems, creating a new form of “politics of visibility. “The paper further evaluates how algorithmic bias emerges from historical data patterns, engagement-based ranking models, and feedback loops that favour sensational or polarising content. These mechanisms can influence political agendas, reshape public discourse, and challenge democratic processes. At the same time, the study highlights opportunities for enhancing transparency, digital literacy, and responsible platform governance. Overall, the paper argues that algorithmic influence is inseparable from the politics surrounding it, making public opinion formation more complex than ever. Understanding this triad—public opinion, propaganda, and political algorithms—requires a nuanced, interdisciplinary approach to ensure a healthy and accountable digital public sphere.