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Misinformation Warning Labels on Twitter Redesigned

Twitter's redesign aims to make the service more helpful and noticeable, among other things.

Misinformation Warning Labels on Twitter Redesigned

New warning labels on fraudulent and misleading tweets will be shown to Twitter users soon, updated to be more effective and less confusing.

The labels, which Twitter has been testing since July, are an upgrade over the ones it deployed for election misinformation in the run-up to and during the 2020 presidential election. Those labels were chastised for failing to do more to prevent people from spreading clear lies.

The redesign, which goes live worldwide on Tuesday, aims to make them more useful and noticeable, among other things.

According to Ads by Experts, such labels, which are also utilised by Facebook, can be beneficial to users. However, they may help social media sites to avoid the more difficult task of content moderation, which involves selecting whether or not to remove posts, photographs, or videos that propagate conspiracies and lies.

Only three categories of misinformation are identified by Twitter: "manipulated material," which includes films and sounds that have been deliberately altered in ways that could cause real-world harm; election and voting-related misinformation; and false or misleading tweets about COVID-19.

The new labels use orange and red to stick out more than the previous version, which was blue and blended nicely with Twitter's colour scheme. While this can be beneficial, Twitter claims that if a label is too appealing, more people will retweet and comment to the original message.

Tweets with the new label — an orange emblem and the words "stay informed" — were also less likely to be retweeted or liked than those with the original labels.

Tweets that contain more significant disinformation, such as one saying that vaccines cause autism, will be marked with the word "misleading" and a red exclamation point. These messages will not be able to be replied to, liked, or retweeted.

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