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Social Recommender Systems

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Recommender Systems Handbook

Abstract

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. We also review related work from the recent years that studied such 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.

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  1. Yahoo Labs, Haifa, Israel

    Ido Guy

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  1. Faculty of Computer Science, Free University of Bozen-Bolzano, Bolzano - Bozen, Italy

    Francesco Ricci

  2. Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Lior Rokach

  3. Ben-Gurion University of the Negev, Beer-Sheva, Israel

    Bracha Shapira

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Guy, I. (2015). Social Recommender Systems. In: Ricci, F., Rokach, L., Shapira, B. (eds) Recommender Systems Handbook. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7637-6_15

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