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What social characteristics enhance recommender systems? The effects of network embeddedness and preference heterogeneity

Author

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  • Feifei He

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education)

  • Chunhua Sun

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education)

  • Yezheng Liu

    (Hefei University of Technology
    Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education)

Abstract

Recommender systems utilize social relationships to improve recommendation performance. This study explores social characteristics and how they affect recommendation performance. We define social characteristics as network embeddedness and preference heterogeneity. Taking rating characteristics as control variables, we build a regression model to explore the impact of two social characteristics on user-level predictive accuracy and the moderating effect of preference heterogeneity on the relationship between network embeddedness and user-level predictive accuracy. The results suggest that network embeddedness positively influences predictive accuracy, whereas preference heterogeneity negatively influences it. Our research reveals that as the preference heterogeneity increases, the positive effect of network embeddedness on predictive accuracy weakens. Preference heterogeneity has a greater impact on user-level predictive accuracy than network embeddedness. Our findings provide management implications for recommender system designers, which is of great significance for improving the accuracy of user-level prediction and reducing user complaints.

Suggested Citation

  • Feifei He & Chunhua Sun & Yezheng Liu, 2023. "What social characteristics enhance recommender systems? The effects of network embeddedness and preference heterogeneity," Electronic Commerce Research, Springer, vol. 23(3), pages 1807-1827, September.
  • Handle: RePEc:spr:elcore:v:23:y:2023:i:3:d:10.1007_s10660-021-09517-5
    DOI: 10.1007/s10660-021-09517-5
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    References listed on IDEAS

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    1. Marc R. Dotson & Joachim Büschken & Greg M. Allenby, 2020. "Explaining Preference Heterogeneity with Mixed Membership Modeling," Marketing Science, INFORMS, vol. 39(2), pages 407-426, March.
    2. Xiaoye Cheng & Jingjing Zhang & Lu (Lucy) Yan, 2020. "Understanding the Impact of Individual Users’ Rating Characteristics on the Predictive Accuracy of Recommender Systems," INFORMS Journal on Computing, INFORMS, vol. 32(2), pages 303-320, April.
    3. Lu (Lucy) Yan & Jianping Peng & Yong Tan, 2015. "Network Dynamics: How Can We Find Patients Like Us?," Information Systems Research, INFORMS, vol. 26(3), pages 496-512, September.
    4. Dan Horsky & Sanjog Misra & Paul Nelson, 2006. "Observed and Unobserved Preference Heterogeneity in Brand-Choice Models," Marketing Science, INFORMS, vol. 25(4), pages 322-335, 07-08.
    5. Liye Ma & Ramayya Krishnan & Alan L. Montgomery, 2015. "Latent Homophily or Social Influence? An Empirical Analysis of Purchase Within a Social Network," Management Science, INFORMS, vol. 61(2), pages 454-473, February.
    6. Chungmok Lee & Minh Pham & Myong K. Jeong & Dohyun Kim & Dennis K. J. Lin & Wanpracha Art Chavalitwongse, 2015. "A Network Structural Approach to the Link Prediction Problem," INFORMS Journal on Computing, INFORMS, vol. 27(2), pages 249-267, May.
    7. Rajdeep Grewal & Gary L. Lilien & Girish Mallapragada, 2006. "Location, Location, Location: How Network Embeddedness Affects Project Success in Open Source Systems," Management Science, INFORMS, vol. 52(7), pages 1043-1056, July.
    Full references (including those not matched with items on IDEAS)

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