Twitter promised on Nov. 2 that it would label tweets that declared a premature victory, but it appears that the platform has escalated to labeling “legal” victories as well.
The company placed an interstitial, or filter, over Senior Advisor to the Trump campaign Jason Miller’s tweet regarding the campaign’s victory today in a Pennsylvania appellate court. Users wanting to see the tweets then have to click “view” in order to see the censored tweets.
Miller tweeted: “Massive legal victory in Philly just now. More to follow shortly,” after a judge in Pennsylvania allowed the campaign “close-up observation of the counting of ballots in the battleground state of Pennsylvania,” according to the New York Post. The win is undeniably a legal victory. How important it is would be opinion — except on Twitter.
The interstitial said “Some or all of the content shared in this Tweet is disputed and might be misleading about an election or other civic process. Learn More.” Twitter has turned off comments and likes on Miller’s tweet, but the platform does still allow quote tweets for the post. The interstitial placed over the tweet said, “Some or all of the content shared in this Tweet is disputed and might be misleading about an election or other civic process. Learn More.”
Just since Nov. 4, Twitter has censored five tweets from President Donald Trump regarding potential election fraud. On Election Day alone, the platform censored content from six different conservatives’ verified accounts. Now, it appears that declaring any victory, even a legal victory, can be flagged as “misleading.” What would Twitter think of the Sweet Victory song from Spongebob?
Conservatives are under attack. Contact Twitter at (415) 222-9670 and demand that Big Tech be held to account to mirror the First Amendment while providing transparency, clarity on “hate speech” and equal footing for conservatives. If you have been censored, contact us at the Media Research Center contact form, and help us hold Big Tech accountable.
via NewsBusters – Exposing Liberal Media Bias
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