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AffRank: Affinity-Driven Ranking of Products in Online Social Rating Networks

Summary: AffRank: Affinity-Driven Ranking of Products in Online Social
Rating Networks
Hui Li, Sourav S. Bhowmick, Aixin Sun
Nanyang Technological University, Nanyang Avenue, Singapore 639798
herolee@pmail.ntu.edu.sg, {assourav,axsun}@ntu.edu.sg
Large online social rating networks (e.g., Epinions, Blippr)
have recently come into being containing information related
to various types of products. Typically, each product in these
networks is associated with a group of members who have pro-
vided ratings and comments on it. These people form a product
community. A potential member can join a product commu-
nity by giving a new rating to the product. We refer to this
phenomenon of a product community's ability to "attract" new
members as product affinity. The knowledge of a ranked list of
products based on product affinity is of much importance to be
utilized for implementing policies, marketing research, online
advertisement, and other applications. In this paper, we iden-
tify and analyze an array of features that exert effect on product
affinity and propose a novel model, called AffRank, that utilizes


Source: Aixin, Sun - School of Computer Engineering, Nanyang Technological University


Collections: Computer Technologies and Information Sciences