Algorithmic Curation and User Engagement: Determining the Effect of Social Media Algorithms on Content Prioritization and User Polarization

The data dissemination through social media platforms has become a key medium. Nevertheless, these platforms depend on intricate algorithmic systems to execute various analytical processes and functions, which are fundamental to algorithmic operations. Algorithms go through large chunks of user data and how users behave in order to maximize user engagement. On the other hand, this infrastructure is developed with the intention of keeping the users on the platform for prolonged periods by serving content, ads and videos that are in sync with a user’s interests or likely to get a response. The research looks into the algorithmic work of social media — specifically, how algorithms of social media curate, filter and prioritize a content based upon user data. This study builds on work that has begun to explore algorithmic processes on social media platforms, focusing on how algorithms combine user data to curate, filter, and frontage content. The analysis is based on textual analysis of the impacts and the influences.