Jia Huang
ABSTRACT
In this paper, we analyze a recommendation network with over 4,000 users and half a million books. There are two types of edges in this network, "read" relations between users and books, and following relations between users. We first investigate in general, if one's followees' recommendations have impacts on one's decision. We then analyze the correlation between one's influence and her centrality in the network. Finally, we study how effective a recommendation is as one sends or receives more and more recommendations. Results show that although in general, one's followee do have an impact over her decision, such influence is not correlated with the followee's centrality. As one receives more and more recommendations for a product, it is more likely that she will accept it. However, there is a saturate point over which more recommendations will have no further impact. As one sends out more and more recommendations, the probabilities that these recommendations get accepted become larger and larger.
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Index Terms
- Information passing in online recommendation
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