Project Veritas Video Shows Former Twitter Employees Discussing 'Shadow Banning' Users

Jake Baker  ·  January 12, 2018  ·  Featured, Media-Entertainment, Elections, Foreign Policy, Middle East, Immigration, Left Wing Ideology, Leftist Bullies


The latest video from James O'Keefe's Project Veritas shows Twitter employees appearing to admit that the platform has "shadow banned" users in the past, and applies its rules and censorship algorithms unevenly in an effort to rid the platform of Trump supporters and conservatives.

In the video, which corroborates previous Breitbart Tech reporting, a former content review agent for Twitter, Mo Norai, appears to admit to banning accounts for political reasons.

"Let's say if it was a pro-Trump thin and I'm anti-Trump. I was like, I banned this whole account."

He goes on to explain how Twitter's "content reviews" are biased against conservatives.

"It goes to you, and then it's at your discretion. And if you're anti-Trump, you're like, 'oh you know what, Mo was right, f**k it, let it go'"

The video also shows Norai agreeing with a Project Veritas reporter that content reviewers would just "let a lot of the left-leaning or liberal stuff go through unchecked."

A former software engineer at Twitter, Abhinav Vadrevu, also appears to admit that Twitter has "shadow banned" users in the past, noting that it's a "risky strategy" and that "in the past, people have been really, really pissed off about that." Vadrevu says he doesn't know if Twitter "does this anymore."

In early 2016, sources told Breitbart Tech that Twitter shadowbanning was "real and happening every day."

The video, which can be watched in full below, also shows how Twitter's machine learning algorithms can classify users as "Russian bots" if their content is too conservative or pro-Trump, and kick them off the platform.

Article source:

Twitter, Josh Mandel, white nationalists, Blacklist, Muting, Mo Norai Engineer, "ANti-Trump Insurance Policy"

Be the first to comment!

To leave a comment, please Login or Register