Social recommender system tutorial

Ido Guy, Werner Geyer

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations


In recent years, with the proliferation of the social web, users are increasingly exposed to social overload and the designers of social web sites are challenged to attract and retain their user basis. Social recommender systems are becoming an integral part of virtually any leading website, playing a key factor in its success: First, they aim to address the overload problem by helping users to find relevant content. Second, they can provide recommendations for content creation, increasing participation and user retention. In this tutorial, we will review the broad domain of social recommender systems, their application for the social web, the underlying techniques and methodologies; the data in use, recommended entities, and target population; evaluation techniques; and open issues and challenges.

Original languageEnglish
Title of host publicationRecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems
PublisherAssociation for Computing Machinery
Number of pages2
ISBN (Electronic)9781450326681
StatePublished - 6 Oct 2014
Externally publishedYes
Event8th ACM Conference on Recommender Systems, RecSys 2014 - Foster City, United States
Duration: 6 Oct 201410 Oct 2014

Publication series

NameRecSys 2014 - Proceedings of the 8th ACM Conference on Recommender Systems


Conference8th ACM Conference on Recommender Systems, RecSys 2014
Country/TerritoryUnited States
CityFoster City


  • Recommender systems
  • Social media
  • Social networks
  • Social recommender systems
  • Social web
  • Web 2.0

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems


Dive into the research topics of 'Social recommender system tutorial'. Together they form a unique fingerprint.

Cite this