Feeds

Google-backed research fights review spam

Seeing through the sockpuppet

Next gen security for virtualised datacentres

University of Illinois at Chicago researchers are taking aim at fake reviews, which they say can seriously damage online businesses.

In particular, the Google-backed study is designed to seek out organized groups of comment fraudsters, and automate the process of identifying and shutting them down.

Fake reviewers can have devastating affects on a variety of Internet-dependent businesses, but with the emergence of user-reviewed social-style operations like Yelp and TripAdvisor, both positive (to promote a business) and negative (to damage a competitor) frauds are becoming endemic.

For the affected business, the researchers say, weeding out the fakes is expensive: while it’s not hard for a human to identify a fraud, the process is labour-intensive.

In their paper, authored by the university’s Bing Liu and Arjun Mukherjee, along with Google’s Natalie Glance, the researchers present an algorithm called GSRank which they hope can be deployed against review fraud.

The key to identifying groups working organized review fraud is their behavior, the paper states, with key fingerprints comprising:

* Time window – members of a group working together to promote or demote a product or service are likely to post reviews within a few days of each other;

* Deviation – naturally, since they’re hired to push a products ratings in a particular direction, an organized group will all post similar ratings. The degree to which the group’s reviews deviate from “genuine” reviews is a hint that someone’s trying to game the system;

* Content similarity – not only will a group give their target the same rating, they’ll also often copy content among themselves. In addition, individuals trying to eke out a living in the cents-per-review business of fraud will have stock phrases that they re-use in different reviews;

* Get in first – the researchers also note that fake reviews will be posted early in the life of a product or service. “Spammers usually review early to make the biggest impact” they write, because “when group members are among the very first people to review a product, they can totally hijack the sentiments”. That behavior can, however, also help identify the fakes;

* Group size – the size of the group, and its size relative to the number of genuine reviews, can both indicate the presence of spammers; and

* “Group support count” – as the researchers note, it’s unlikely that the same (say) 10 random individuals would repeatedly find themselves reviewing many different products; so to have the same group turning up across many different products also helps indicate spammers.

The researchers note that they can’t tell the difference between multiple individuals working together, or one “sockpuppet” user operating multiple user IDs. However, since their algorithm is looking at behavior rather than identity, that shouldn’t matter. ®

The essential guide to IT transformation

More from The Register

next story
Goog says patch⁵⁰ your Chrome
64-bit browser loads cat vids FIFTEEN PERCENT faster!
Chinese hackers spied on investigators of Flight MH370 - report
Classified data on flight's disappearance pinched
KER-CHING! CryptoWall ransomware scam rakes in $1 MEEELLION
Anatomy of the net's most destructive ransomware threat
NIST to sysadmins: clean up your SSH mess
Too many keys, too badly managed
Scratched PC-dispatch patch patched, hatched in batch rematch
Windows security update fixed after triggering blue screens (and screams) of death
Researchers camouflage haxxor traps with fake application traffic
Honeypots sweetened to resemble actual workloads, complete with 'secure' logins
prev story

Whitepapers

Top 10 endpoint backup mistakes
Avoid the ten endpoint backup mistakes to ensure that your critical corporate data is protected and end user productivity is improved.
Implementing global e-invoicing with guaranteed legal certainty
Explaining the role local tax compliance plays in successful supply chain management and e-business and how leading global brands are addressing this.
Backing up distributed data
Eliminating the redundant use of bandwidth and storage capacity and application consolidation in the modern data center.
The essential guide to IT transformation
ServiceNow discusses three IT transformations that can help CIOs automate IT services to transform IT and the enterprise
Next gen security for virtualised datacentres
Legacy security solutions are inefficient due to the architectural differences between physical and virtual environments.