Title
REV2: Fraudulent User Prediction in Rating Platforms.
Abstract
Rating platforms enable large-scale collection of user opinion about items(e.g., products or other users). However, untrustworthy users give fraudulent ratings for excessive monetary gains. In this paper, we present REV2, a system to identify such fraudulent users. We propose three interdependent intrinsic quality metrics---fairness of a user, reliability of a rating and goodness of a product. The fairness and reliability quantify the trustworthiness of a user and rating, respectively, and goodness quantifies the quality of a product. Intuitively, a user is fair if it provides reliable scores that are close to the goodness of products. We propose six axioms to establish the interdependency between the scores, and then, formulate a mutually recursive definition that satisfies these axioms. We extend the formulation to address cold start problem and incorporate behavior properties. We develop the REV2 algorithm to calculate these intrinsic quality scores for all users, ratings, and products. We show that this algorithm is guaranteed to converge and has linear time complexity. By conducting extensive experiments on five rating datasets, we show that REV2 outperforms nine existing algorithms in detecting fair and unfair users. We reported the 150 most unfair users in the Flipkart network to their review fraud investigators, and 127 users were identified as being fraudulent(84.6% accuracy). The REV2 algorithm is being deployed at Flipkart.
Year
DOI
Venue
2018
10.1145/3159652.3159729
WSDM 2018: The Eleventh ACM International Conference on Web Search and Data Mining Marina Del Rey CA USA February, 2018
Field
DocType
ISBN
Interdependence,Data mining,Cold start,Computer science,Axiom,Crowdsourcing,Time complexity,Instrumental and intrinsic value,Stochastic control,Recursive definition
Conference
978-1-4503-5581-0
Citations 
PageRank 
References 
30
0.82
29
Authors
6
Name
Order
Citations
PageRank
Srijan Kumar132624.97
bryan hooi228728.70
disha makhija3591.96
mohit kumar4693.19
Christos Faloutsos5279724490.38
V. S. Subrahmanian668641053.38