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An algorithm developed at Carnegie Mellon University makes it easier to determine if someone has faked an Amazon or Yelp review or if a politician with a suspiciously large number of Twitter followers might have bought and paid for that popularity.
The method, called FRAUDAR, marks the latest escalation in the cat-and-mouse game played by online fraudsters and the social media platforms that try to out them. In particular, the new algorithm makes it possible to see through camouflage that fraudsters use to make themselves look legitimate, said Christos Faloutsos, professor of machine learning and computer science.
In real-world experiments using Twitter data for 41.7 million users and 1.47 billion followers, FRAUDAR fingered more than 4,000 accounts not previously identified as fraudulent, including many that used known follower-buying services such as TweepMe and TweeterGetter.
Bad news for the nascent astroturfing industry.
(Score: 0) by Anonymous Coward on Friday September 09 2016, @04:06PM
Hmmmm, I just wonder what would be revealed if this algorithm were turned on the current set of Presidential candidates. Would we suddenly find that Trump's supporters are mostly just his personal sock puppets? Would we find that Hillary shows her strongest support amongst Democrat party operatives? Would we see Johnson suddenly narrow the gap between himself and the main party candidates? I would be really interested to see someone look into this.
(Score: 2) by maxwell demon on Friday September 09 2016, @05:07PM
Maybe it would find that Trump and Clinton themselves are both fake.
The Tao of math: The numbers you can count are not the real numbers.