Research of Fraud Review Detection Model on O2O Platform
LI Jing1, WU Guo-shi1, XIE Fei2, YAO Xu1, QI Jia-yin3, SUN Peng-fei1
1. School of Software Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China;
2. Communication and Technical Bureau, Xinhua News Agency, Beijing 100803, China;
3. School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China
Living-consumption platform has become a very important platform for customers to extract information of businesses,and view or submit comments on the quality of services or products.It is common that fake reviews,as a commercial activity,are used to exaggerate or damage the reputation of a target business,which is extremely harmful.This paper chose an O2O (Online To Offline) platform,from which reviews are derived,to study fake reviews.With an in-depth study on features of fake reviews,it raised the user-credibility and shop-credibility evaluation model respectively from the credibility perspective.Based on features of reviewers,businesses,and review texts,it established a fake review identification model,and through testing this model showed excellent performance in identification.
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