Social networks have become very important for networking, communications, and content sharing. Social networking applications generate a huge amount of data on a daily basis and social networks constitute a growing field of research, because of the heterogeneity of data and structures formed in them, and their size and dynamics. When this wealth of data is leveraged by recommender systems, the resulting coupling can help address interesting problems related to social engagement, member recruitment, and friend recommendations.In this work we review the various facets of large-scale social recommender systems, summarizing the challenges and interesting problems and discussing some of the solutions.
Magdalini Eirinaki, Jerry Gao, Iraklis Varlamis, and Konstantinos Tserpes. "Recommender Systems for Large-Scale Social Networks: A review of challenges and solutions" Future Generation Computer Systems (2018): 413-418. doi:10.1016/j.future.2017.09.015