Finding Deceptive Opinion Spam by Any Stretch of the Imagination

Understand

Consumers increasingly rate, review and research products online.

• Consequently, websites containing consumer reviews are becoming targets of opinion spam.
• While recent work has focused primarily on manually identifiable 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 psychology and computational linguistics, we develop and compare three approaches to detecting deceptive opinion spam, and ultimately develop a classifier that is nearly 90% accurate on our gold-standard opinion spam dataset.