We propose using profile compatibility to differentiate genuine and fake product reviews. For each product, a collective profile is derived from a separate collection of reviews. Such a profile contains a number of aspects of the product, together with their descriptions. For a given unseen review about the same product, we build a test profile using the same approach. We then perform a bidirectional alignment between the test and the collective profile, to compute a list of aspect-wise compatible features. We adopt Ott et al. (2011)
REF worked with n-grams features and deep syntax features to differentiate genuine and fake product reviews.
Detecting Deceptive Opinions with Profile Compatibility
IJCNLP
Computer Science