Trump, Obama, Among Those Most Impacted By Twitter Purge

President Donald Trump and former President Barack Obama were among the political and celebrity names most impacted by this week’s purge of locked accounts on Twitter.



Photo Credit: Twitter

Twitter began deleting locked accounts on Wednesday, impacting the follower number for countless users, particularly some of the most prominent politicians and celebrities that use the social media platform.

Officials said that locked accounts occur when they see sudden changes in behavior. They then reach out to the owners of the accounts and unless they validate the account and reset their passwords, they stay locked with no ability to log in.

With the purge ongoing, Obama has lost more than 2.5 million followers, down to approximately 101 million, while Trump saw his follower count decrease by 400,000, dropping him to 53.1 million followers. 

Other celebrities hundreds of thousands of followers, some millions, including Twitter CEO Jack Dorsey, who posted that he lost 200,000 followers in 24 hours.

In a blog posted on Wednesday, Vijaya Gadde, Twitter’s director of legal, policy, trust and safety, said that “most people will see a change of four followers or fewer; others with larger follower counts will experience a more significant drop. We understand this may be hard for some, but we believe accuracy and transparency make Twitter a more trusted service for public conversation.”

“Though the most significant changes are happening in the next few days, follower counts may continue to change more regularly as part of our ongoing work to proactively identify and challenge problematic accounts.”

Gadde specified that locked accounts on Twitter are different than spam accounts or “bots.”

“In most cases, these accounts were created by real people but we cannot confirm that the original person who opened the account still has control and access to it. Spam accounts (sometimes referred to as bots) typically exhibit spammy behavior from the beginning, are increasingly predictable by our systems, and can be automatically shut down with our technology.”

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