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Twitter announced on Monday its intention to step up its fight against vaccine misinformation, including the ability to ban users after five reminders.

“We believe that this warning system will help educate the public on our regulations and better reduce the spread of potentially dangerous or misleading information […], especially for repeated, moderate or serious infractions,” the social network said. in a press release.

In December, the platform 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.

8,400 tweets removed

Since then, the moderators of the California-based 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 twelve hours.

On the fourth warning, the blockage will last for seven 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.

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.

Labels on messages

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 "which may contain misleading information about Covid-19 vaccines," according to Monday's press release.

Moderators will be responsible for determining which content violates the regulations.

However, the platform hopes to develop a system that is both human and automated to detect problematic messages.

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