Project Veritas Drops 2nd Undercover Video – Twitter Engineers Brag About Banning Pro-Trump
Channel: BreakingNews365
Date: 11/01/2018

Project Veritas Drops 2nd Undercover Video – Twitter Engineers Brag About Banning Pro-Trump Accounts.

Source and content: https://goo.gl/XTuerT
Early Wednesday morning, Project Veritas revealed Twitter is willing to hand over President Trump’s private messages to the Justice Department without a search warrant.

O’Keefe’s 2nd undercover video shows Twitter employees talking about how they target pro-Trump accounts by banning them or hiding their content.

O’Keefe released a video Wednesday afternoon warning about the next video release exposing Twitter.

“Tomorrow we have multiple employees at Twitter talking specifically how they censor people for their ideas and some of the engineering involved,” O’Keefe said.
Via Project Veritas:

Steven Pierre, Twitter engineer explains “shadow banning,” says “it’s going to ban a way of talking”

Former Twitter software engineer Abhinav Vadrevu on shadow banning: “they just think that no one is engaging with their content, when in reality, no one is seeing it”

Former Twitter Content Review Agent Mo Norai explains banning process: “if it was a pro-Trump thing and I’m anti-Trump… I banned his whole account… it’s at your discretion”

When asked if banning process was an unwritten rule, Norai adds “Very. A lot of unwritten rules… It was never written it was more said”

Olinda Hassan, Policy Manager for Twitter Trust and Safety explains, “we’re trying to ‘down rank’… shitty people to not show up,” “we’re working [that] on right now”

“Shadow banning” to be used to stealthily target political views- former Twitter engineer says, “that’s a thing”

Censorship of certain political viewpoints to be automated via “machine learning” according to Twitter software engineer

Parnay Singh, Twitter Direct Messaging Engineer, on machine learning algorithms, “you have like five thousand keywords to describe a redneck…” “the majority of it are for Republicans”

Video via Project Veritas:
On January 3rd 2018 at a San Francisco restaurant, Abhinov Vadrevu, a former Twitter Software Engineer explains a strategy, called “shadow banning,” that to his knowledge, Twitter has employed:

“One strategy is to shadow ban so you have ultimate control. The idea of a shadow ban is that you ban someone but they don’t know they’ve been banned, because they keep posting and no one sees their content. So they just think that no one is engaging with their content, when in reality, no one is seeing it.”

Twitter is in the process of automating censorship and banning, says Twitter Software Engineer Steven Pierre on December 8th of 2017:

“Every single conversation is going to be rated by a machine and the machine is going to say whether or not it’s a positive thing or a negative thing. And whether it’s positive or negative doesn’t (inaudible), it’s more like if somebody’s being aggressive or not. Right? Somebody’s just cursing at somebody, whatever, whatever. They may have point, but it will just vanish… It’s not going to ban the mindset, it’s going to ban, like, a way of talking.”

Olinda Hassan, a Policy Manager for Twitter’s Trust and Safety team explains on December 15th, 2017 at a Twitter holiday party that the development of a system of “down ranking” “shitty people” is in the works:

“Yeah. That’s something we’re working on. It’s something we’re working on. We’re trying to get the shitty people to not show up. It’s a product thing we’re working on right now.”

Former Twitter Engineer Conrado Miranda confirms on December 1st, 2017 that tools are already in place to censor pro-Trump or conservative content on the platform. When asked whether or not these capabilities exist, Miranda says, “that’s a thing.”

In a conversation with former Twitter Content Review Agent Mo Norai on May 16th, 2017, we learned that in the past Twitter would manually ban or censor Pro-Trump or conservative content. When asked about the process of banning accounts, Norai said, “On stuff like that it was more discretion on your view point, I guess how you felt about a particular matter…”

When asked to clarify if that process was automated Norai confirmed that it was not:

“Yeah, if they said this is: ‘Pro-Trump’ I don’t want it because it offends me, this, that. And I say I banned this whole thing, and it goes over here and they are like, ‘Oh you know what? I don’t like it too. You know what? Mo’s right, let’s go, let’s carry on, what’s next?’”

Norai also revealed that more left-leaning content would go through their selection process with less political scrutiny, “It would come through checked and then I would be like ‘Oh you know what? This is okay. Let it go.’”

Norai explains that this selection process wasn’t exactly Twitter policy, but rather they were following unwritten rules from the top: