Abstract
Internet auctions are one of the few successful new business models. Owing to the nature of Internet auctions, e.g. high degree of anonymity, relaxed legal constraints, and low costs for entry and exit, etc..., fraudsters are easily to setup a scam or deception in auction activities. Undeniable fact is that information asymmetry between sellers and buyers and lacking of immediately examining authenticity of the merchandise, the buyer can’t verify the seller and the characteristics of the merchandise until after the transaction is completed. This paper proposes a simple method which is detected potential fraudster by social network analysis (SNA) and decision tree to provide a feasible mechanism of playing capable guardians in buyers’ auction activities. Through our simple method, buyers can easily avoid defraud in auction activities.
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References
van Heck, E., Vervest, P.: How Should CIOs Deal With Web-Based Auction? Communication of the ACM 41(7), 99–100 (1998)
National Fraud Information Center: Internet Fraud Statistics Reports (2005), Available from http://www.fraud.org/internet/intstat.htm
Anderson, K.B.: Internet Auction Fraud: What Can We Learn From Consumer Sentinel Data? Federal Trade Commission Report (2004)
National Consumer League Internet Fraud Watch (2000-2005), Internet Fraud Statistics (2005), Available from http://www.fraud.org/internet/intstat.htm
Chua, C.E.H., Wareham, J.: Self-Regulation for Online Auctions: An Analysis. In: Proc. 23rd Int’l Conf. Information Systems, pp. 115–125. Assoc. for Information Systems (2002)
Kauffman, R.J., Wood, C.A.: Premium Bidding in Online Auctions: An Examination of Opportunism and Seller Preference (2006), Available from http://www.mgmt.purdue.edu/academics/mis/workshop/kw_111805.pdf
Chua, C.E.H., Wareham, J.: Fighting Internet Auction Fraud: An Assessment and Proposal. IEEE Computer 37(10), 31–37 (2004)
Resnick, P., et al.: Reputation Systems. Communication of the ACM 43(12), 45–48 (2000)
Resnick, P., Zeckhauser, R.: Trust among Strangers in Internet Transactions: Empirical Analysis of eBay’s Reputation System. Advances in Applied Microeconomics 11, 127–157 (2002)
Houser, D., Wooders, J.: Reputation in Auctions: Theory, and Evidence from eBay. Journal of Economics & Management Strategy 15(2), 353–370 (2006)
Gregg, D.G., Scott, J.E.: The Role of Reputation Systems in Reducing On-Line Auction Fraud. International Journal of Electronic Commerce 10(3), 95–120 (2006)
Ba, S., et al.: Choice of Transaction Channels: The Effects of Product Characteristics on Market Evolution. Journal of Management Information Systems 21(4), 173–197 (2005)
Ba, S., Whinston, A.B., Zhang, H.: Building trust in online auction markets through an economic incentive mechanism. Decision Support Systems 35(3), 273–286 (2003)
Dolan, K.M.: Internet Auction Fraud: The Silent Victims. Journal of Economic Crime Management 2(1), 1–22 (2004)
National White Collar Crime Center, IC3 2005 Internet Crime Report (2005), Available from http://www.nw3c.org/
Wang, J.C., Chiu, C.C., Ker, H.Y.: Detecting Online Auction Fraud of Reputation Inflation through Social Network Structures Embedded in Transaction Records. Journal of Information Management (Taiwan) 12(4), 144–184 (2004)
Haythornthwaite, C.: Social Network Analysis: An Approach and Technique for the Study of Information Exchange. Library & Information Science Research 18(4), 323–342 (1996)
Scott, J.: Social Network Analysis. SAGE Publications, London (2000)
Xu, J., Chen, H.: CrimeNet Explorer: A Framework for Criminal Network Knowledge Discovery. ACM Transactions on Information Systems 23(2), 201–226 (2005)
Xu, J., Chen, H.: Criminal network analysis and visualization. Communication of the ACM 48(6), 100–107 (2005)
Seidman, S.B.: Network Structure and minimum degree. Social Networks, 267-287 (1983)
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Ku, Y., Chen, Y., Chiu, C. (2007). A Proposed Data Mining Approach for Internet Auction Fraud Detection. In: Yang, C.C., et al. Intelligence and Security Informatics. PAISI 2007. Lecture Notes in Computer Science, vol 4430. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71549-8_22
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DOI: https://doi.org/10.1007/978-3-540-71549-8_22
Publisher Name: Springer, Berlin, Heidelberg
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