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Twitter bans Steve Bannon's podcast account following beheading comments
YouTube also pulled the episode in question.
Twitter has permanently banned Steve Bannon’s podcast after he suggested that Dr. Anthony Fauci and former FBI director Christopher Wray should be beheaded, according to CNBC. “The... account has been permanently suspended for violating the Twitter Rules, specifically our policy on the glorification of violence,” a spokesperson told CNBC.
Bannon made the comments while free on a $5 million bond after being accused of defrauding donors to a non-profit group trying to build a wall on the southern US border. “Second term kicks off with firing Wray, firing Fauci,” Bannon said on the podcast, referring to the election. “I’d actually like to go back to the old times of Tudor England, I’d put the heads on pikes, right, I’d put them at the two corners of the White House as a warning to federal bureaucrats. You either get with the program or you’re gone — time to stop playing games.”
“Mr. Bannon’s commentary was clearly meant metaphorically,” a Bannon spokesperson said. “He previously played a clip of St. Thomas More’s trial and was making an allusion to this historical event in Tudor England for rhetorical purposes.”
YouTube also banned the episode, though not the entire podcast. A three strikes policy means that the channel is still available, though videos can’t be uploaded for at least a week. “We’ve removed this video for violating our policy against inciting violence,” spokesperson Alex Joseph told MSNBC. “We will continue to be vigilant as we enforce our policies in the post-election period.”
Bannon has been accused in the past of making outrageous comments to attract attention and test the limits of social networks. With the election results still unfolding and tensions rising, however, sites like Twitter, TikTok, Facebook and YouTube have been clamping down on content that could incite violence. That has included limiting or blocking posts completely, adding warning messages and more. YouTube, for example, tweaked its famous recommendation algorithms to slow down borderline content, while promoting authoritative sources.
