A Study on the Impact of Social Media Algorithms on News Consumption Patterns

Abstract

With the widespread adoption of social media, algorithmic recommendation systems have become pivotal in news dissemination,
profoundly reshaping users information consumption patterns. This study examines how these algorithms fundamentally influence news
delivery methods, user information access, content distribution efficiency, and news credibility through their core operational principles.
Supported by case studies and empirical data, it explores both opportunities and challenges posed by algorithmic technologies. The research
reveals that while enhanced information matching efficiency, these systems also create echo chambers and cognitive biases, undermining journalistic objectivity and public accountability.