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Twitter to ban users for repeated vaccine misinformation


Twitter on Monday announced plans to step up its fight against vaccine misinformation, including the ability to ban users after five reminders. “We believe this warning system will help educate the public about our regulations and better reduce the spread of potentially dangerous or misleading information on Twitter, especially for repeated, moderate or serious breaches,” the tweet network said. in a press release.

In December, Twitter had already decided to ask users to remove some false claims, including those suggesting that vaccines are used to harm or control populations. It also targeted lies about alleged adverse effects or questioning of the very existence of Covid-19 and the need to be vaccinated. Since then, the moderators of the Californian company have removed more than 8,400 tweets and notified some 11.5 million accounts worldwide.

Now, from the second warning, users will have their account blocked for 12 hours. At the fourth warning, the block will last 7 days. In the fifth, it will become permanent. This system is inspired by the one against disinformation linked to elections and civic processes, which notably led Twitter to ban former US President Donald Trump for repeated offenses such as incitement to violence and his messages discrediting the presidential ballot.

Youtube and Facebook have also taken action

Vaccination campaigns against Covid-19, necessary to protect populations and allow the resumption of human activities, are underway in many countries, from the United States to the European Union. As early as October, when vaccines were only in clinical testing, YouTube and Facebook announced strict regulations to ban vaccine misinformation and efforts to harm vaccination campaigns.

Twitter will also put labels on messages “that may contain misleading information about Covid-19 vaccines,” according to Monday’s statement. Moderators will be responsible for determining which content violates the regulations, but the platform hopes to develop a system that is both human and automated to detect problematic messages.



Source site www.europe1.fr

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