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A Social Network-Based Recommender System (SNRS)

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Data Mining for Social Network Data

Part of the book series: Annals of Information Systems ((AOIS,volume 12))

Abstract

Social influence plays an important role in product marketing. However, it has rarely been considered in traditional recommender systems. In this chapter, we present a new paradigm of recommender systems which can utilize information in social networks, including user preferences, item’s general acceptance, and influence from social friends. A probabilistic model is developed to make personalized recommendations from such information. We extract data from a real online social network, and our analysis of this large data set reveals that friends have a tendency to select the same items and give similar ratings. Experimental results on this data set show that our proposed system not only improves the prediction accuracy of recommender systems but also remedies the data sparsity and cold-start issues inherent in collaborative filtering. Furthermore, we propose to improve the performance of our system by applying semantic filtering of social networks and validate its improvement via a class project experiment. In this experiment we demonstrate how relevant friends can be selected for inference based on the semantics of friend relationships and finer-grained user ratings. Such technologies can be deployed by most content providers.

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Acknowledgments

The authors would like to thank Professor Zhuowen Tu and Mr. Jiayan Jiang of UCLA for their stimulating discussions in statistical modeling of social networks.

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Authors and Affiliations

  1. Computer Science Department, University of California, Los Angeles, CA, 90095, USA

    Jianming He & Wesley W. Chu

Authors
  1. Jianming He
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  2. Wesley W. Chu
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Corresponding author

Correspondence to Jianming He .

Editor information

Editors and Affiliations

  1. , Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Campusvej 55, Odense M, 5230, Denmark

    Nasrullah Memon

  2. , Dept. Computer Information Systems, Bentley University, Forest St. 175, Waltham, 02452, USA

    Jennifer Jie Xu

  3. , Dept. Computer Science & Engineering, Aalborg University Esbjerg, Niels Bohrs Vej 8, Esbjerg, 6700, Denmark

    David L. Hicks

  4. Eller College of Management, University of Arizona, E. Helen St. 1130, Tucson, 85721, Arizona, USA

    Hsinchun Chen

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He, J., Chu, W.W. (2010). A Social Network-Based Recommender System (SNRS). In: Memon, N., Xu, J., Hicks, D., Chen, H. (eds) Data Mining for Social Network Data. Annals of Information Systems, vol 12. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-6287-4_4

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