DocumentCode :
593751
Title :
Detecting review spam: Challenges and opportunities
Author :
Yingying Ma ; Fengjun Li
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of Kansas, Lawrence, KS, USA
fYear :
2012
fDate :
14-17 Oct. 2012
Firstpage :
651
Lastpage :
654
Abstract :
Online customer reviews for both products or merchants have greatly affected others´ decision making in purchase. Considering the easily accessibility of the reviews and the significant impacts to the retailers, there is an increasing incentive to manipulate the reviews, mostly profit-driven. Without proper protection, spam reviews will cause gradual loss of credibility of the reviews and corrupt the entire online review systems eventually. Therefore, review spam detection is considered as the first step towards securing the online review systems. In this paper, we aim to overview existing detection approaches in a systematic way, define key research issues, and articulate future research challenges and opportunities for review spam detection.
Keywords :
consumer behaviour; decision making; purchasing; unsolicited e-mail; credibility loss; incentives; online customer merchant review system security; online customer product review system security; profit-driven review manipulation; purchase decision making; review spam detection; Sun; World Wide Web; Review spam; review spammer; spam behavior;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom), 2012 8th International Conference on
Conference_Location :
Pittsburgh, PA
Print_ISBN :
978-1-4673-2740-4
Type :
conf
Filename :
6450964
Link To Document :
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