Detecting imprudence of 'reliable' sellers in online auction sites
Reputation systems deployed in popular online auction sites simply aggregate feedback about a seller's past transactions. By studying a real auction site dataset, we infer that a non-negligible fraction of unsatisfactory transactions involve sellers with high reputation. Such a phenomenon can b...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/101077 http://hdl.handle.net/10220/16771 |
| _version_ | 1811691373604110336 |
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| author | Liu, Xin Datta, Anwitaman Fang, Hui Zhang, Jie |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Liu, Xin Datta, Anwitaman Fang, Hui Zhang, Jie |
| author_sort | Liu, Xin |
| collection | NTU |
| description | Reputation systems deployed in popular online auction sites simply aggregate feedback about a seller's past transactions. By studying a real auction site dataset, we infer that a non-negligible fraction of unsatisfactory transactions involve sellers with high reputation. Such a phenomenon can be interpreted by motivation theory from behaviorial science: A seller with high reputation has more business opportunities. Bad feedback for latest transactions do not immediately affect his reputation adequately to hurt business, hence he may not be as prudent as before. In this work, we propose the concept of imprudence to study and detect the inappropriate behavior of a 'reliable' seller (i.e., the one with high reputation computed using conventional approaches). Specifically, we first identify and verify the features that influence a seller's imprudence behavior. We then design a novel intelligent buying agent to combine these factors using logistic regression for predicting and studying the probability of imprudence of a target seller. We validate our approach using real datasets driven experiments. |
| first_indexed | 2024-10-01T06:18:52Z |
| format | Conference Paper |
| id | ntu-10356/101077 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:18:52Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/1010772020-05-28T07:17:30Z Detecting imprudence of 'reliable' sellers in online auction sites Liu, Xin Datta, Anwitaman Fang, Hui Zhang, Jie School of Computer Engineering IEEE International Conference on Trust, Security and Privacy in Computing and Communications (11th : 2012 : Liverpool, UK) DRNTU::Engineering::Computer science and engineering Reputation systems deployed in popular online auction sites simply aggregate feedback about a seller's past transactions. By studying a real auction site dataset, we infer that a non-negligible fraction of unsatisfactory transactions involve sellers with high reputation. Such a phenomenon can be interpreted by motivation theory from behaviorial science: A seller with high reputation has more business opportunities. Bad feedback for latest transactions do not immediately affect his reputation adequately to hurt business, hence he may not be as prudent as before. In this work, we propose the concept of imprudence to study and detect the inappropriate behavior of a 'reliable' seller (i.e., the one with high reputation computed using conventional approaches). Specifically, we first identify and verify the features that influence a seller's imprudence behavior. We then design a novel intelligent buying agent to combine these factors using logistic regression for predicting and studying the probability of imprudence of a target seller. We validate our approach using real datasets driven experiments. 2013-10-24T06:35:56Z 2019-12-06T20:33:07Z 2013-10-24T06:35:56Z 2019-12-06T20:33:07Z 2012 2012 Conference Paper Liu, X., Datta, A., Fang, H., & Zhang, J. (2012). Detecting imprudence of 'reliable' sellers in online auction sites. 2012 IEEE 11th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), pp.246-253. https://hdl.handle.net/10356/101077 http://hdl.handle.net/10220/16771 10.1109/TrustCom.2012.123 en |
| spellingShingle | DRNTU::Engineering::Computer science and engineering Liu, Xin Datta, Anwitaman Fang, Hui Zhang, Jie Detecting imprudence of 'reliable' sellers in online auction sites |
| title | Detecting imprudence of 'reliable' sellers in online auction sites |
| title_full | Detecting imprudence of 'reliable' sellers in online auction sites |
| title_fullStr | Detecting imprudence of 'reliable' sellers in online auction sites |
| title_full_unstemmed | Detecting imprudence of 'reliable' sellers in online auction sites |
| title_short | Detecting imprudence of 'reliable' sellers in online auction sites |
| title_sort | detecting imprudence of reliable sellers in online auction sites |
| topic | DRNTU::Engineering::Computer science and engineering |
| url | https://hdl.handle.net/10356/101077 http://hdl.handle.net/10220/16771 |
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