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Twitter is working to “improve” its labelling process related to Covid-19 and 5G content following reports of the platform mislabelling relevant information as misinformation.
“In the last few weeks, you may have seen Tweets with labels linking to additional info about Covid-19. Not all of those Tweets had potentially misleading content associating Covid-19 and 5G. We apologize for any confusion and we're working to improve our labelling process,” Twitter wrote on its Twitter Support account.
The platform detailed its policies related to misinformation about the pandemic and stated that it adds labels to content in order to provide more context to users.
“Our policies prohibit sharing false or misleading content related to Covid-19, as this could lead to harm,” it wrote.
“We may also use labels with links to additional context and information to help keep you informed about misleading or disputed topics,” it added.
“To show context about these topics where it’s likely to be useful, we're building new automated capabilities to apply these labels to Tweets we think could be relevant.
As we improve this process to be more precise, our goal is to show fewer labels on unrelated Tweets,” it further added.
Earlier this month, the micro-blogging platform had begun adding fact-check labels to tweets linking 5G with the outbreak of the Covid-19 pandemic.
The platform adds a label that reads "Get the facts about Covid-19" to such tweets. The label is linked with a Twitter page titled “No, 5G isn’t causing coronavirus” which provides information debunking this theory with links to news reports, fact-checking organizations, and government agencies.
“Numerous people have been spreading unsubstantiated stories about 5G technology being linked to the spread of Covid-19. The theory has been debunked by several reputable sources including government officials, and experts in the tech and medical industries,” the page description reads.
Twitter had earlier had updated its guidelines on unverified claims related to 5G. It will now improve this process to decrease the mislabelling of content.
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