Research on the Mechanism of Social Platform Algorithms Influencing Public Information Cognition

With the rapid development of social platforms, algorithm recommendation has gradually become an important way for users to obtain online information. When changing the user's information exposure range, it will also have an impact on their understanding and judgment of information. This article takes social platform users as the research object to explore the internal mechanism of algorithmic factors affecting public information cognition. This article verifies the validity of 377 questionnaires through reliability and validity analysis, regression analysis, and mediation effect test. The research results indicate that algorithmic perception has a significant negative impact on information cognitive bias, while algorithmic transparency and algorithmic control significantly affect users' information cognitive bias. Further analysis reveals that algorithmic perception and algorithmic control generate partial mediating effects through platform trust, while algorithmic transparency generates complete mediating effects through platform trust. Research shows that social platform algorithms not only affect the way users receive information, but also influence their information judgment process through their trust in the platform.