Analyzing Social Networks of Sport Preferences for Personalized Recommendations

This study is conducted as part of the development of the MoveUs application, which aims to provide users with personalized recommendations for sports activities and potential training partners. To achieve this, we investigate how Social Network Analysis (SNA) can be applied to recommendation systems. The study is based on an experiment using data collected through a survey of 119 participants, capturing their sport preferences and engagement in activities. From this data, three different network variants were constructed, each representing distinct aspects of user interactions and participation in sports activities. SNA metrics were then applied to analyse the global network structure, identify communities, and detect central nodes across all three networks. The results were examined to determine which network measures can be leveraged for personalized recommendations. This preliminary study demonstrates the potential of integrating SNA into the development of personalized recommendation systems within the MoveUs application.