Comment classification for Internet auction platforms
T. Kaszuba, A. Hupa, and A. Wierzbicki. Local Proceedings of 13th East-European Conference, ADBIS 2009, page 374-384. JUMI Pubbbblishing House Ltd., (2009)
Abstract
Reducing Internet auction fraud is one of the greatest challenges
in today’s electronic
market. Most of the electronic auction platforms use only simple reputation
system
that can be easily manipulated. Although reputation systems can be
used to
detect frauds, they provide little detailed information about the
fraud itself except user
comments. Significant experience is required to understand every aspect
of
Internet auctions. Despite many help pages and tutorials provided
by auction platforms,
in most cases it is not easy to teach users how to protect themselves
from Internet fraud.
When all negative comments are treated equally by reputation algorithms,
it is impossible to distinguish between malicious behavior and accidental
mistakes.
Our goal is to design automatic comment classification methods that
will allow a meaningful distinction of different types of negative
and neutral comments. We have developed a hierarchical model of user
behavior in Internet auctions (separately for buyers and sellers).
By checking the frequency of occurrence and the significance of reported
transaction problems we have created simple classification method
to detect potential threats related to users’ transactions. We have
also proposed method of rating complaints against sellers and buyers
that can be used to modify the Internet auction reputation algorithms.
%0 Conference Paper
%1 Kaszuba2009a
%A Kaszuba, Tomasz
%A Hupa, Albert
%A Wierzbicki, Adam
%B Local Proceedings of 13th East-European Conference, ADBIS 2009
%D 2009
%I JUMI Pubbbblishing House Ltd.
%K auctions classification complaints fraud textmining webmining
%P 374-384
%T Comment classification for Internet auction platforms
%X Reducing Internet auction fraud is one of the greatest challenges
in today’s electronic
market. Most of the electronic auction platforms use only simple reputation
system
that can be easily manipulated. Although reputation systems can be
used to
detect frauds, they provide little detailed information about the
fraud itself except user
comments. Significant experience is required to understand every aspect
of
Internet auctions. Despite many help pages and tutorials provided
by auction platforms,
in most cases it is not easy to teach users how to protect themselves
from Internet fraud.
When all negative comments are treated equally by reputation algorithms,
it is impossible to distinguish between malicious behavior and accidental
mistakes.
Our goal is to design automatic comment classification methods that
will allow a meaningful distinction of different types of negative
and neutral comments. We have developed a hierarchical model of user
behavior in Internet auctions (separately for buyers and sellers).
By checking the frequency of occurrence and the significance of reported
transaction problems we have created simple classification method
to detect potential threats related to users’ transactions. We have
also proposed method of rating complaints against sellers and buyers
that can be used to modify the Internet auction reputation algorithms.
@inproceedings{Kaszuba2009a,
abstract = {Reducing Internet auction fraud is one of the greatest challenges
in today’s electronic
market. Most of the electronic auction platforms use only simple reputation
system
that can be easily manipulated. Although reputation systems can be
used to
detect frauds, they provide little detailed information about the
fraud itself except user
comments. Significant experience is required to understand every aspect
of
Internet auctions. Despite many help pages and tutorials provided
by auction platforms,
in most cases it is not easy to teach users how to protect themselves
from Internet fraud.
When all negative comments are treated equally by reputation algorithms,
it is impossible to distinguish between malicious behavior and accidental
mistakes.
Our goal is to design automatic comment classification methods that
will allow a meaningful distinction of different types of negative
and neutral comments. We have developed a hierarchical model of user
behavior in Internet auctions (separately for buyers and sellers).
By checking the frequency of occurrence and the significance of reported
transaction problems we have created simple classification method
to detect potential threats related to users’ transactions. We have
also proposed method of rating complaints against sellers and buyers
that can be used to modify the Internet auction reputation algorithms.},
added-at = {2009-10-08T00:52:53.000+0200},
author = {Kaszuba, Tomasz and Hupa, Albert and Wierzbicki, Adam},
biburl = {https://www.bibsonomy.org/bibtex/2015d7ca27ed90f7f425054a5c6f678f5/utrust_user},
booktitle = {Local Proceedings of 13th East-European Conference, ADBIS 2009},
interhash = {5bc6b4be03d8ec1717cbb36b90ac7bf4},
intrahash = {015d7ca27ed90f7f425054a5c6f678f5},
keywords = {auctions classification complaints fraud textmining webmining},
pages = {374-384},
publisher = {JUMI Pubbbblishing House Ltd.},
timestamp = {2009-10-08T00:52:53.000+0200},
title = {Comment classification for Internet auction platforms},
year = 2009
}