In recent years, algorithm-driven media platforms have reshaped how people encounter political information, often amplifying extreme narratives. While this has made political content more accessible, it has also raised questions about its impact on trust in democratic institutions. This paper looks at the psychological processes behind this phenomenon, focusing on how exposure to algorithmically selected extremist content shapes attitudes, emotions, and intergroup relations.



The study brings together ideas from political psychology, cognitive psychology, and media research to ask a central question: how does algorithmic influence affect people's sense of trust in democracy? Using a mixed-methods approach, the research combines experimental simulations of algorithmic feeds with surveys measuring trust, perceived fairness of algorithms, and vulnerability to misinformation. It also examines protective factors such as critical thinking skills, media literacy, and resilience strategies that may reduce susceptibility to extremist influence.


By approaching the problem from a transdisciplinary perspective, the project aims not only to identify risks but also to highlight interventions that could strengthen democratic trust. The hope is to move beyond describing the dangers of algorithmic extremism toward practical insights that psychologists, educators, and policymakers can use to foster more informed and engaged citizens. This research points to the importance of collaboration across psychology, technology, and governance in addressing the psychological challenges of political life in the digital era.