Finding Unusual Review Patterns Using Unexpected Rules
Conference Proceeding Article
In recent years, opinion mining attracted a great deal of research attention. However, limited work has been done on detecting opinion spam (or fake reviews). The problem is analogous to spam in Web search [1, 9 11]. However, review spam is harder to detect because it is very hard, if not impossible, to recognize fake reviews by manually reading them . This paper deals with a restricted problem, i.e., identifying unusual review patterns which can represent suspicious behaviors of reviewers. We formulate the problem as finding unexpected rules. The technique is domain independent. Using the technique, we analyzed an Amazon.com review dataset and found many unexpected rules and rule groups which indicate spam activities.
Reviewer behavior, review spam, unexpected patterns
Databases and Information Systems | Numerical Analysis and Scientific Computing
Data Management and Analytics
CIKM '10: Proceedings of the 19th ACM international conference on Information and knowledge management
City or Country
JINDAL, Nitin; LIU, Bing; and LIM, Ee Peng.
Finding Unusual Review Patterns Using Unexpected Rules. (2010). CIKM '10: Proceedings of the 19th ACM international conference on Information and knowledge management. 1549-1552. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/625
This document is currently not available here.