Discovering Fake Consumer Reviews With GSRank
Researchers are working on ways to discover fake reviews by detecting organised groups of review spammers.
Basic Pattern of Fake Reviews
Observing a small group of three fake reviewers/accounts lead to the following findings:
- Same product reviewed by the common group.
- High rating by group members.
- Narrow time window within all rated products.
- Group reviewed the same set of products.
- Quick to rate. Usually first or among first to review.
The first step in product review analysis is to build a reference dataset. This involves data mining followed by labelling and defining group spam behaviour indicators. Group and individual behavioural statistics are examined and ranking experiments are conducted to train the system. The evaluated results are not only fast but also highly accurate.
This research don’t only help stores (Amazon) and their customers but it also carries much wider potential. Search engines can now apply GSRank model to discover fake reviews and normalise their aggregate ratings for products, places and various other features.
 Mukherjee, A., Liu, B., Glance, N., – Spotting Fake Reviewer Groups in Consumer Reviews, WWW 2012, April 16–20, 2012, Lyon, France.