Implementation of Recommendation Algorithms in Social Media Applications to Form Urban Community Social Networks

Abstract

Implementation of recommendation algorithms in social media applications to create social networks in urban communities using social media that is evenly distributed in urban life, an understanding of how recommendation algorithms can be utilized to expand and strengthen social networks is becoming increasingly needed. Recommendation algorithms have a complex role in facilitating meaningful interactions within social media platforms, tailored specifically to the dynamics of urban environments. Through a mixed approach that combines literature analysis and empirical investigation, this research explains the impact of recommendation algorithms on social interactions in digital environments. These algorithms play an important role in filtering relevant content and enabling individuals to connect with like-minded people, thereby driving the expansion of social networks. However, challenges related to privacy and the risks of establishing closed information spaces were also identified. This research highlights the importance of finding a balance between harnessing the power of recommendation algorithms to improve social networks and protecting user privacy and information diversity. These implications are not only relevant for social media developers, but also for policymakers and other stakeholders involved in designing inclusive and sustainable digital environments for urban communities.