Blog
About

  • Record: found
  • Abstract: found
  • Article: found
Is Open Access

“The Devil You Know Knows Best” – How Online Recommendations Can Benefit From Social Networking

, ,

Proceedings of HCI 2007 The 21st British HCI Group Annual Conference University of Lancaster, UK (HCI)

British HCI Group Annual Conference

3 - 7 September 2007

Recommender systems, online advice-seeking, social networking, decision support

Read this article at

Bookmark
      There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

      Abstract

      The defining characteristic of the Internet today is an abundance of information and choice. Recommender Systems (RS), designed to alleviate this problem, have so far not been very successful, and recent research suggests that this is due to the lack of the social context and inter-personal trust. We simulated an online film RS with 60 participants, where recommender information was added to the recommendations, and a subset of these were attributed to friends of the participants. Participants overwhelmingly preferred recommendations from familiar recommenders with whom they shared interests and a high rating overlap. When recommenders were familiar, rating overlap was the most important decision factor, whereas when they were unfamiliar, the combination of profile similarity and rating overlap was important. We recommend that RS and social networking functionality should be integrated, and show how RS functionality can be added to an existing social networking system by visualising profile similarity.

      Related collections

      Most cited references 10

      • Record: found
      • Abstract: not found
      • Article: not found

      Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions

        Bookmark
        • Record: found
        • Abstract: not found
        • Article: not found

        An algorithmic framework for performing collaborative filtering

          Bookmark
          • Record: found
          • Abstract: not found
          • Article: not found

          Trust in recommender systems

            Bookmark

            Author and article information

            Affiliations
            University College London

            Department of Computer Science

            Gower Street

            London WC1E 6BT
            University College London

            Department of Psychology

            Gower Street

            London WC1E 6BT
            Contributors
            Conference
            September 2007
            September 2007
            : 1-11
            10.14236/ewic/HCI2007.8
            © Philip Bonhard et al. Published by BCS Learning and Development Ltd. Proceedings of HCI 2007 The 21st British HCI Group Annual Conference University of Lancaster, UK

            This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

            Proceedings of HCI 2007 The 21st British HCI Group Annual Conference University of Lancaster, UK
            HCI
            21
            Lancaster, UK
            3 - 7 September 2007
            Electronic Workshops in Computing (eWiC)
            British HCI Group Annual Conference
            Product
            Product Information: 1477-9358 BCS Learning & Development
            Self URI (journal page): https://ewic.bcs.org/
            Categories
            Electronic Workshops in Computing

            Comments

            Comment on this article