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.