Social Recommender Systems

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

3 Scopus citations


Recommender systems play an increasingly important role in the success of social media websites. Higher portions of social websites’ traffic are triggered by recommendations and those sites rely on the quality of the recommendations to attract new users and retain existing ones. In this chapter, we introduce the notion of social recommender systems as recommender systems that target the social media domain. After a short introduction, we discuss in detail two of the most prominent types of social recommender systems-recommendation of social media content and recommendation of people. We describe the main approaches and state-of-the-art techniques for each of the recommendation types. Among these, is the use of explicit social relations reflected in social network sites to boost recommendation quality and cope with the cold start problem. We also review related work that studied social recommender systems, in order to demonstrate the different use cases and methods applied to take advantage of the unique data. We conclude by summarizing the key aspects, emerging domains, and open challenges for social recommender systems.

Original languageEnglish
Title of host publicationRecommender Systems Handbook
Subtitle of host publicationThird Edition
PublisherSpringer US
Number of pages36
ISBN (Electronic)9781071621974
ISBN (Print)9781071621967
StatePublished - 1 Jan 2022

ASJC Scopus subject areas

  • Computer Science (all)


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