TY - GEN
T1 - Towards online review spam detection
AU - Lin, Yuming
AU - Zhu, Tao
AU - Wang, Xiaoling
AU - Zhang, Jingwei
AU - Zhou, Aoying
N1 - Publisher Copyright:
© Copyright 2014 by the International World Wide Web Conferences Steering Committee.
PY - 2014/4/7
Y1 - 2014/4/7
N2 - User reviews play a crucial role in Web, since many decisions are made based on them. However, review spam would misled the users, which is extremely obnoxious. In this poster, we explore the problem of online review spam detection. Firstly, we devise six features to find the spam based on the review content and re- viewer behaviors. Secondly, we apply supervised methods and an unsupervised one for spotting the review spam as early as possible. Finally, we carry out intensive experiments on a real-world review set to verify the proposed methods.
AB - User reviews play a crucial role in Web, since many decisions are made based on them. However, review spam would misled the users, which is extremely obnoxious. In this poster, we explore the problem of online review spam detection. Firstly, we devise six features to find the spam based on the review content and re- viewer behaviors. Secondly, we apply supervised methods and an unsupervised one for spotting the review spam as early as possible. Finally, we carry out intensive experiments on a real-world review set to verify the proposed methods.
KW - Online detection
KW - Review analysis
KW - Review spam
UR - https://www.scopus.com/pages/publications/84990944695
U2 - 10.1145/2567948.2577293
DO - 10.1145/2567948.2577293
M3 - 会议稿件
AN - SCOPUS:84990944695
T3 - WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web
SP - 341
EP - 342
BT - WWW 2014 Companion - Proceedings of the 23rd International Conference on World Wide Web
PB - Association for Computing Machinery, Inc
T2 - 23rd International Conference on World Wide Web, WWW 2014
Y2 - 7 April 2014 through 11 April 2014
ER -