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Facebook reveals the AI tool it used to ban 6.6 billion fake accounts

2020-03-04 18:35 by


Facebook's engineers have developed a more efficient machine-learning tool, which has already helped take down 6.6 billion fake accounts in the last year. And that number doesn't even include the additional "millions" of "attempts" to create fake accounts that are blocked daily, according to Bochra Gharbaoui, data science manager at Facebook.

Deep Entity Classification (DEC) is a machine learning model that doesn't just take into account the activity of the suspect account, but it also evaluates all of the surrounding information, including the behaviors of the accounts and pages the suspect account interacts with. Facebook says it's reduced the estimated volume of spam and scam accounts by 27 percent.

The tech giant distinguishes between two types of fake accounts. First there are "user-misclassified accounts," personal profiles for businesses or pets that are meant to be Pages. These are relatively straightforward to deal with—they just get converted to Pages. "Violating accounts," on the other hand, are more serious. These are personal profiles that engage in scamming and spamming or otherwise violate the platform's terms of service. Violating accounts need to be removed as quickly as possible without casting too wide a net and snagging real accounts as well.

Five years ago, Facebook relied largely on users to flag offending accounts to human reviewers. But the volume of problematic accounts Facebook has to deal with is massive: in the third quarter of 2019, the last period for which the company has released numbers, Facebook blocked some 1.7 billion offending accounts. And that doesn't even include accounts the company prevents from ever being created in the first place. At any time, Facebook estimates that 5% of its active accounts are fraudulent.

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