Computer Science ›› 2014, Vol. 41 ›› Issue (10): 295-299.doi: 10.11896/j.issn.1002-137X.2014.10.062

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Detecting Product Review Spammers Based on Review Graphs

WANG Zhuo,LI Zhun,XU Ye and SONG Kai   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Online product reviews can significantly affect product sales,resulting in a large number of reviewers who promote and/or demote target products by writing untruthful product reviews.Wang G et al proposed review graphs which reveal the relationships of reviews,reviewers and stores to calculate the reputations of reviews,reviewers and stores by convergent iterative computation,which can capture fake reviewers.To handle the storeless shopping environment,we proposed a new review graph structure by replacing stores with products,and designed a novel Algorithm ICE to fasten the iteration process by eliminating a certain portion of reviewers and reviews during each iteration.Meanwhile,by exploiting new scoring criteria for reviews,reviewers and products,the precision for identifying fake reviewers is also improved.Experiments show that the proposed Algorithm ICE not only performs faster but also more accurately than previous method.

Key words: Fake review,Review graph,Opinion mining

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