Paper: Finding Deceptive Opinion Spam by Any Stretch of the Imagination

ACL ID P11-1032
Title Finding Deceptive Opinion Spam by Any Stretch of the Imagination
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2011
Authors

Consumers increasingly rate, review and re- search products online (Jansen, 2010; Litvin et al., 2008). Consequently, websites con- taining consumer reviews are becoming tar- gets of opinion spam. While recent work has focused primarily on manually identifi- able instances of opinion spam, in this work we study deceptive opinion spam—fictitious opinions that have been deliberately written to sound authentic. Integrating work from psy- chology and computational linguistics, we de- velop and compare three approaches to detect- ing deceptive opinion spam, and ultimately develop a classifier that is nearly 90% accurate on our gold-standard opinion spam dataset. Based on feature analysis of our learned mod- els, we additionally make several theoretical contributions, including revealing a rel...