The Role of Social Media Algorithms in Shaping the Information Environment and Human Cognition

Social media platforms have fundamentally transformed the contemporary information environment by replacing traditional editorial gatekeeping with algorithmically driven content personalization. Rather than presenting identical information to all users, digital platforms selectively prioritize content according to individual behavioural patterns, interests, and previous online interactions. While previous studies have extensively examined algorithmic filtering, echo chambers, and filter bubbles, comparatively limited attention has been devoted to understanding how algorithmic personalization interacts with cognitive biases to influence users’ perception and interpretation of information. This study addresses this research gap by investigating the relationship between algorithmic personalization, information exposure, and perception formation within social media environments.

A convergent mixed-methods research design was employed, integrating quantitative and qualitative approaches. The quantitative phase consisted of an online survey administered to 100 social media users aged 18-65 years, while the qualitative phase involved semi-structured interviews with eight professionals working in social media management, marketing, and political communication. Quantitative data were analysed using descriptive statistical methods, whereas qualitative data were analysed through thematic analysis following Braun and Clarke’s (2006) framework.

The findings demonstrate that social media constitutes the primary source of information for the majority of respondents and that algorithmic personalization substantially influences users’ perceived relevance of information, selective exposure, and trust in digital content. Although respondents generally expressed high levels of confidence in algorithmic recommendation systems, they simultaneously supported greater transparency and stronger user control over algorithmic decision-making. Interview findings further revealed that professionals perceive algorithms as mechanisms that reinforce confirmation bias, increase emotional engagement, fragment public discourse, and contribute to the construction of individualized information environments.

The study argues that algorithmic influence should not be interpreted as a deterministic process through which technology directly controls human thinking. Rather, algorithmic personalization functions as a cognitive amplification mechanism that systematically reinforces existing behavioural tendencies and cognitive biases by continuously optimizing personalized information exposure. By integrating perspectives from communication studies, cognitive psychology, and digital media research, this article contributes to a more comprehensive understanding of the mechanisms through which algorithmic systems shape perception within contemporary digital societies.