WHATSAPP BANNING OVER 2 MILLION ACCOUNTS EACH MONTH

whatsapp banned million of fake accounts

Whatsapp said in a statement that they banned over six million accounts in previous 3 months as it’s an effort fighting against fake news and platform abuse. Whatsapp currently has over 1.5 billion monthly active users. Whatsapp said the they has developed sophisticated machine learning system, that detect abusive behavior and ban suspicious account during messaging and in response to reported by other users.

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“Our goal is to identify and stop abusive accounts as quickly as possible, which is why identifying these accounts manually is not realistic. Instead, we have advanced machine learning systems that take action to ban accounts, 24 hours a day, 7 days a week,” said the company.

HOW IT WORKS?

According to Whatsapp, this whole process works in three stages – at registration, during messaging and in response to negative feedback, which company receive in the form of report and blocks.

REGISTRATION STAGE : In this process all users need to verify themselves by entering a 6 digit code at the time registration. “Since all accounts must go through registration before being able to send any messages, it is an effective starting point to concentrate our efforts.”

MESSAGING STAGE : According to Whatsapp, the system evaluates that how users behave in real time. The chat app bans account on the basis of the intensity of user activity. “Spammers attempting to automate messaging may lack the technical ability to forge this typing indicator. If an account continually sends messages without triggering the typing indicator, it can be a signal of abuse, and we will ban the account,” says the company.

REPORT OR NEGATIVE FEEDBACK : ” When a user sends a report, our machine learning systems review and categorize the reports so we can better understand the motivation of the account, such as whether they are trying to sell a product or seed is information. This new information not only helps us ban accounts, but it also helps us improve our machine learning systems to take earlier action in the future (such as at registration or while messaging, as described above).”

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