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Twitter Reviewing How To Make Misinformation Labels More Obvious And Direct

Twitter Reviewing How To Make Misinformation Labels More Obvious And Direct
The look and working of the labels that the micro blogging site Twitter applies to misinformation are being reconsidered by it as a part of the efforts of the company to try and make these interventions more obvious to its users and reduce its reaction times to such posts, said e company’s head of site integrity in an interview to the news agency Reuters.
The aim of the company is to make the small blue notices which it attaches to posts and tweets that it deems to be false or misleading more 'overt' and be more 'direct' in giving users information and it is looking at changing those notices, said Twitter's Yoel Roth. He however did not confirm whether any change would be implemented by the company prior to the presidential elections in the United States which will take place in about a month. Analysts expect that this period could be used extensively for the spreading of false and misleading online content.
Testing out a more visible reddish-magenta color for the notices and deciding on whether to point out users who consistently post false information are among the new efforts that the company is reviewing, Roth said.
"We've definitely heard the feedback that it would be useful to see if an account is a repeat offender or has been repeatedly labeled, and we're thinking about the options there," said Roth.
After a public feedback period, flagging and labeling of manipulated or fabricated media or content was started by Twitter in early 2020. It later also included misinformation about the novel coronavirus pandemic in its labeling for misleading tweets and later added misleading tweets about elections and civic processes. Even though the company now claims that it has already labeled thousands of posts, analysts and critics have attached most attention to the labels applied to tweets that were made by the US President Donald Trump.
Posts claiming election victory before results were certified would be labeled or removed, Twitter had announced in September.
One of the factors that has prompted Twitter to rethink how its labels could be more obvious is research that have busted the myth or the concept that people's beliefs in misinformation can be strengthened by correction- a phenomenon which has been called the 'backfire effect', Roth said.
For Twitter, the risk of labeling tweets is that it could "become a badge of honor" which could prompt or motivate users to actively pursue this path for gaining more attention on the platform, Roth said.
There have been criticisms from researchers of the Twitter's labels as being too slow, some misinformation experts have praised the effort by the company as a long-overdue intervention.
"Mostly things take off so fast that if you wait 20 or 30 minutes... most of the spread for someone with a big audience has already happened," said Kate Starbird, an associate professor at the University of Washington who has been analyzing Twitter's labeling responses.

Christopher J. Mitchell

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