How can algorithmic filtering on social media most significantly contribute to the formation of echo chambers?

Algorithmic filtering on social media most significantly contributes to the formation of echo chambers by selectively curating content based on a user's past behavior and preferences, thereby reinforcing existing beliefs and limiting exposure to diverse perspectives. Social media algorithms are designed to maximize user engagement by showing content that is most likely to be liked, shared, or commented on. This often results in users being primarily exposed to information that confirms their existing views and perspectives, while dissenting opinions or alternative viewpoints are filtered out. This creates an echo chamber where users are primarily hearing their own views echoed back to them, reinforcing their beliefs and making them less likely to encounter or consider opposing viewpoints. This selective exposure can lead to increased polarization and a decreased ability to critically evaluate information from different perspectives.