Twitter is testing how its misinformation labels can be
more obvious, direct
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[October 06, 2020] By
Elizabeth Culliford
(Reuters) - Twitter is rethinking how the
labels it applies to misinformation look and work, its head of site
integrity told Reuters in an interview, as the social media company
tries to make these interventions more obvious and cut its reaction
times.
Twitter's Yoel Roth said the company is exploring changes to the small
blue notices that it attaches to certain false or misleading tweets, to
make these signals more 'overt' and be more 'direct' in giving users
information. But he did not say whether any new versions would be ready
before the U.S. election in the next four weeks, a period that experts
say could be rife with false and misleading online content.
Roth said the new efforts at Twitter include testing a more visible
reddish-magenta color, and working out whether to flag users who
consistently post false information.
"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.
Twitter started labeling manipulated or fabricated media in early 2020,
after a public feedback period. It expanded its labels to coronavirus
misinformation and then to misleading tweets about elections and civic
processes. Twitter says it has now labeled thousands of posts, though
most attention has been on the labels applied to tweets by U.S.
President Donald Trump.
In September, Twitter announced it would label or remove posts claiming
election victory before results were certified.
Roth said research undermining the idea that corrections can strengthen
people's beliefs in misinformation - known as the 'backfire effect' -
had contributed to Twitter rethinking how its labels could be more
obvious. The risk is that label
"becomes a badge of honor" that users actively pursue for attention,
said Roth. Though Twitter's labels have been praised by some
misinformation experts as a long-overdue intervention, their execution
has triggered criticisms from researchers as too slow.
"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.
It took Twitter about eight hours to add labels to Trump tweets about
mail-in voting the first time it labeled him in May, though Starbird
said Twitter was getting quicker. Two Trump tweets in September appeared
to have been labeled within two hours.
Roth said Twitter reduces the reach of all tweets labeled for
misinformation, by limiting their visibility and not recommending them
in places like search results. The company declined to share any data
about the effectiveness of these steps.
[to top of second column] |
U.S. President Donald Trump speaks at the White House after
returning from hospitalization at the Walter Reed Medical Center for
coronavirus disease (COVID-19) treatment, in Washington, October 5,
2020, in this still image from video posted on Trump's Twitter page.
@realDonaldTrump/Handout via REUTERS
In August, Election Integrity Partnership researchers said Twitter's disabling
retweets on a Trump tweet that violated its rules had a clear effect on its
spread but was "too little, too late." Roth said Twitter takes into account the
number of retweets, engagement and views to prioritize viral content for review
to give "the most bang for our buck." But he said Twitter was exploring how to
predict which tweets would go viral and conducting exercises on likely new 2020
election claims to get faster.
Multiple researchers told Reuters it was difficult to assess effectiveness of
Twitter's interventions without knowing which actions it was taking and when.
The company does not keep public lists of when it has applied labels and has not
shared data to allow outsiders to assess how its labels affect a tweet's spread
or how users interact with them. "The platforms need to explain what hypothesis
they're testing, how they're testing it, what the results are and be
transparent," said Tommy Shane, head of policy and impact at anti-misinformation
non-profit First Draft. "Because these are public experiments."
TRUMP TWEETS
Twitter has labeled or put gray warning overlays over ten @realDonaldTrump
tweets for reasons related to civic integrity rules since it first labeled him
in May.
Roth said Twitter consults with partners, including election officials, on its
labeling. But it has chosen to link to a page of tweets from multiple sources
rather than follow Facebook's lead of paying third-party fact-checkers -
including Reuters - to assess content as they could be 'easy to dismiss if you
disagree with them.'
Facebook Inc <FB.O>, which exempts politicians from its fact-checking program
and faced backlash for not acting on misleading Trump posts, has started adding
labels with voting information to all related posts. This strategy has been
criticized by researchers for not quickly and obviously differentiating between
true and false.
Trump spokeswoman Samantha Zager said in a statement, without offering specific
evidence, that "across social media platforms, it's clear the Silicon Valley
Mafia creates arbitrary rules that do not apply equally to every account and
instead are used to silence any views in opposition to those held by the liberal
Big Tech coastal elites."
Asked how Twitter is monitoring high-profile users like Trump or his Democratic
presidential rival Joe Biden, Roth said Twitter does not "specifically focus in
on individual accounts or individual account holders."
(Reporting by Elizabeth Culliford; Editing by Greg Mitchell and Edward Tobin)
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