Paper: Towards a General Rule for Identifying Deceptive Opinion Spam

ACL ID P14-1147
Title Towards a General Rule for Identifying Deceptive Opinion Spam
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

Consumers? purchase decisions are in- creasingly influenced by user-generated online reviews. Accordingly, there has been growing concern about the poten- tial for posting deceptive opinion spam? fictitious reviews that have been deliber- ately written to sound authentic, to de- ceive the reader. In this paper, we ex- plore generalized approaches for identify- ing online deceptive opinion spam based on a new gold standard dataset, which is comprised of data from three different do- mains (i.e. Hotel, Restaurant, Doctor), each of which contains three types of re- views, i.e. customer generated truthful re- views, Turker generated deceptive reviews and employee (domain-expert) generated deceptive reviews. Our approach tries to capture the general difference of language usage between deceptiv...