This study examines how different social media algorithmic feeds influence users' engagement patterns and belief formation when encountering news content.
Participants are randomly assigned to one of three experimental conditions, each representing a different content ranking algorithm. The study investigates how these algorithms affect information consumption, belief updating, and perceived credibility.
Content is ranked by chronological order, showing the most recent posts first. This condition serves as a baseline for understanding how users engage with temporally-ordered information feeds.
View SurveyContent is ranked by engagement metrics (likes, retweets, comments). This condition examines how popularity-based ranking affects information consumption and belief formation.
View SurveyContent is ranked by source credibility and factual accuracy. This condition investigates how epistemic quality-based ranking influences user engagement and trust in information.
View SurveyYou will be randomly assigned to one of the three conditions. Please click the button below to begin the survey, or select a specific condition above for preview purposes.