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Study Finds ‘Collusion Network’ of Fake Likes on Facebook

Lucinda Shen
By
Lucinda Shen
Lucinda Shen
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Lucinda Shen
By
Lucinda Shen
Lucinda Shen
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September 9, 2017, 12:10 PM ET
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This Nov. 21, 2016 file photo shows the Facebook logo on a laptop and a smartphone.Justin Tallis—AFP/Getty Images

A Facebook post that quickly receives lots of likes is also more likely to be seen by more users.

But researchers at the University of Iowa and the Lahore University of Management found that at least 1 million fake and real Facebook accounts have gamed the system by entering a “collusion network” that has created at least 100 million likes. The study was conducted in the run up to the 2016 presidential election, the results of which some claim were impacted by fake news on Facebook.

According to the researchers, accounts can sign up for “reputation manipulation services,” and enter these networks. By signing up, members grant the services the ability to like and comment on the posts of other members—allowing the services to use the full force of its network to boost certain posts and accounts.

“Such collusion networks of significant size enable members to receive a large number of likes from other members, making them appear much more popular than they actually are,” the researchers wrote.

Facebook has been in the limelight since the 2016 elections, with some saying that fake news shared on the social media site helped influence the elections. Earlier this week, Facebook also announced that an influence operation likely based out of Russia had spent $100,000 since May 2015 on ads that backed socially and politically polarizing views on the site.

The researchers said they were not able to determine if these collusion networks were used to influence the 2016 presidential elections, or if Russia was in any way involved.

“We do want to examine the Russia question,” Zubair Shafiq, a co-author, told CBS News.

Facebook was made aware of the findings in May 2016, with Facebook developing ways to manage the collusion networks.

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Lucinda Shen
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