Social recommender systems have recently become one of the hottest topics in the domain of recommender systems. The main task of social recommender system is to alleviate data sparsity and cold-start problems, and improve its performance utilizing users' social attributes. This paper presents an overview of the field of social recommender systems, including trust inference algorithms, key techniques and typical applications. The prospects for future development and suggestions for possible extensions are also discussed.