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Source Factors in Recommender System Credibility Evaluation

  • Chapter
Recommender Systems Handbook

Abstract

Although recommender system research in the last decade has provided significant insight into how users interact with and evaluate systems, the social role of recommender systems as advice givers has been largely neglected. By conceptualizing the advice seeking and giving relationship as a fundamentally social process, important avenues for understanding the persuasiveness of recommender systems open up. Specifically, research regarding the influence of source characteristics, which is abundant in the context of human-human communication, can provide an important framework for identifying potential influence factors. This chapter reviews the existing literature on source factors in the context of human-human, human-technology, and human-recommender system interactions. It also discusses system credibility evaluation in light of the increasing popularity of social technology. It concludes that many social cues that have been identified as influential in other contexts have yet to be implemented and tested with respect to recommender systems. Implications for recommender system research and design are discussed.

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Authors and Affiliations

  1. William Paterson University, 300 Pompton Road, Wayne, NJ, USA

    Kyung-Hyan Yoo

  2. University of Queensland, Sir Fred Schonell Drive, St. Lucia, Brisbane, QLD, 4072, Australia

    Ulrike Gretzel

  3. Alpen-Adria-Universitaet Klagenfurt, Universitaetsstrasse 65, 9020, Klagenfurt, Austria

    Markus Zanker

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  1. Kyung-Hyan Yoo
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  2. Ulrike Gretzel
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  3. Markus Zanker
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Correspondence to Kyung-Hyan Yoo .

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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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Yoo, KH., Gretzel, U., Zanker, M. (2015). Source Factors in Recommender System Credibility Evaluation. In: Ricci, F., Rokach, L., Shapira, B. (eds) Recommender Systems Handbook. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7637-6_20

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