An empirical analysis of return on investment maximization in sponsored search auctions
Proceedings of the 2nd International Workshop on Data Mining and Audience Intelligence for Advertising
Meme-tracking and the dynamics of the news cycle
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 10th ACM conference on Electronic commerce
Empirical price modeling for sponsored search
WINE'07 Proceedings of the 3rd international conference on Internet and network economics
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Online peer-to-peer (P2P) lending services are a new type of social platform that enables individuals borrow and lend money directly from one to another. In this paper, we study the dynamics of bidding behavior in a P2P loan auction website, Prosper.com. We investigate the change of various attributes of loan requesting listings over time, such as the interest rate and the number of bids. We observe that there is herding behavior during bidding, and for most of the listings, the numbers of bids they receive reach spikes at very similar time points. We explain these phenomena by showing that there are economic and social factors that lenders take into account when deciding to bid on a listing. We also observe that the profits the lenders make are tied with their bidding preferences. Finally, we build a model based on the temporal progression of the bidding, that reliably predicts the success of a loan request listing, as well as whether a loan will be paid back or not.