Recommender System for Social Media: Research Challenges and Future Applications

Social networks have evolved as a ubiquitous means of communication in our daily lives. Users consistently generate a large amount of data on social media platforms, which on the other hand has increased the complexity when selecting relevant social media content. Thus, recommender system has been emerged as a solution to provide personalized and user-centric media recommendations. However, social media has significantly broadened the scope of available inputs such as social sensing data and new types of social media. It not only offers new research opportunities for social media recommender systems, but also indicates that various domains may benefit from the application of social media recommender systems. Therefore, this paper conducts a comprehensive survey of state-of-the-art research between social media and recommender systems. The survey results identify a set of research challenges on how social media recommender systems can be applied in various domains such as healthcare and route planning.