Merging multiple criteria to identify suspicious reviews

Authors:
Guangyu Wu;Derek Greene;Pádraig Cunningham
Affiliations:
University College Dublin, Dublin, Ireland;University College Dublin, Dublin, Ireland;University College Dublin, Dublin, Ireland
Venue:
Proceedings of the fourth ACM conference on Recommender systems
Year:
2010

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Abstract

Assessing the trustworthiness of reviews is a key issue for the maintainers of opinion sites such as TripAdvisor, given the rewards that can be derived from posting false or biased reviews. In this paper we present a number of criteria that might be indicative of suspicious reviews and evaluate alternative methods for integrating these criteria to produce a unified "suspiciousness" ranking. The criteria derive from characteristics of the network of reviewers and also from analysis of the content and impact of reviews and ratings. The integration methods that are evaluated are singular value decomposition and the unsupervised hedge algorithm. These alternatives are evaluated in a user study on TripAdvisor reviews, where volunteers were asked to rate the suspiciousness of reviews that have been highlighted by the criteria.