Fake accounts have plagued, and is continuously plaguing the Internet up to this day. They spread spam and phishing links, as well as malwares that can damage computers. Thankfully, social media platforms who combat these fake accounts, like Facebook, who took down an average of 2 billion fake accounts last year. The question is, how do they know which are fake accounts? Facebook reveals how they do it.
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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.
To do this, Facebook uses hand-coded rules and machine learning to block a fake account either before it is created or before it becomes active. In other words, before it can harm real users. The final stage is after a fake account has gone live. This is when detection gets a lot trickier and where the new machine-learning system, known as Deep Entity Classification (DEC), comes in.
More details about this over at Technology Review.
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Source: neatorama