Social Recommender System

When examining the interplay of information system, individual, and social networks, I focus on a specific type of information system – the recommender system. This is because this type of information system is widely distributed in the online environment and is closely related to and affecting individual’s online experience. There is a heated debate on the effect of recommender systems on consumer preference – whether it is homogenizing or diversifying consumer preferences. One of my projects on this domain targets on this issue and extends prior studies by examining a new type of recommender system, the social recommender system, which incorporates users’ social network information when providing recommendations. This paper draws on the structural view of social networks, social influence theories, and human information processing theories to develop specific hypotheses and empirically test whether social recommender systems homogenize or diversify consumer preferences. This paper is currently under second round review at Information Systems Research.

Another related project is a literature review and discussion of recommender systems in general. This study synthesizes extant empirical IS studies to provide a coherent view of recommender systems research and identify gaps for future research. Authors group their review around three major stages of research in recommender systems that emerge from our review: understand consumer, recommendation presentation, and recommender system’s impacts. This paper was published at the Journal of Association for Information Systems in 2015. The two projects above are both collaborated with Dr. Elena Karahanna from the University of Georgia.

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