Spotting Fake Consumer Reviews and Reviewers

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Fake Reviews

Product reviews are now widely used by individuals and organizations for their decision making. If one sees many positive reviews of the product, one is very likely to buy the product. However, if one sees many negative reviews, he/she will most likely choose another product. Positive opinions can result in significant financial gains and/or fames for organizations and individuals. This, unfortunately, gives good incentives for opinion spam.

However, due to the reason of profit more and more people are trying to game the system by writing fake reviews to harm or promote some products or services. A fake review means that it is either a positive review written by the business owners themselves (or people they contract to write reviews) or a negative review written by a business’s competitors.

Below is a compendium of studies, explanations and resources on how to spot fake consumer reviews on products, hotels, restaurants, etc.

Google is investing part of its resources to support a research project at the University of Illinois in Chicago that aims to identify fraudulent commentary aimed at harming or promote a product or service.

One of the main goals is precisely the search for organized groups of people who comment fraudulently together to promote or denigrate any kind of products on the Internet, so that you can automate the process of identifying them and delete these comments and their associated accounts .

The fake reviews and analysis can have devastating effects on all types of Internet businesses and the promotion of social services like Yelp or TripAdvisor recommendation made that user feedback on both the negative and the positive become endemic.

Researchers have presented an algorithm called GSRank they believe may offer certain guarantees to combat these types of fraud, based on various tracks. Among them, the date range of comments, good or bad comments usually occur in a short space of time, or the diversion/distribution of those grades-many similar qualifications will suspect that product or service.

In the study published by researchers can reveal some of the factors that help to detect such fraud GSRank, and hope that this will make markedly decrease these behaviors on the Internet.

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.

In the words of Dan Petrovic in his post Discovering Fake Consumer Reviews With GSRank:

This research does not only help stores or sites, like Amazon, Yelp or TripAdvisor, and their customers but it also carries much wider potential. Search engines can now apply GSRank model to discover fake reviews and normalize their aggregate ratings for products, places and various other features.

Check out some articles exposing as finding ways to detect fake reviews

How to pick up deceptive cues online by obvious patterns on reviews

Fake Review

And check out this interesting answer from a former Yelp worker, who is asked about “What fraction of Yelp reviews are fake?

Read Quote of Jack Stahl’s answer to What fraction of Yelp reviews are fake? on Quora

References


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This entry was posted in CRO, E-commerce, Recommended by Cristian Guasch. Bookmark the permalink.

About Cristian Guasch

Cristian Guasch is a Organic Search and Conversion Optimizer at The Cocktail in Madrid, and also is the SEO Lead for MSN Spain, both job titles since January 2011. In MSN, his responsibilities include engage with the SEO Lead of EMEA, and implement the SEO best practices, strategies and tactics, meet targets, and ensure that SEO requirements are fully integrated with editorial and engineering processes.He has been involved with the online and search marketing projects since 2008 and worked with all types of businesses; from small to enterprise companies. Prior to joining MSN team, he was the responsible of the Online Marketing and the Ecommerce Manager of a small company called SEMIC.