Election 2020

Facebook and Twitter are finally calling out election misinformation. Is it working?

It's unclear if labels are effectively limiting the spread of falsehoods.

Facebook and Twitter are finally calling out election misinformation. Is it working?

Facebook is applying the same label to all posts from both Biden and Trump, which some might find confusing.

Image: Facebook

Over the past 24 hours, both Twitter and Facebook have slapped a relentless stream of labels on misleading posts about voting and election results — most prominently from the president himself.

Misinformation researchers have praised some of their efforts. But a much larger question hangs over each of these decisions: Do these labels even work?

Some preliminary studies have found that warning labels on fake news stories can have the unintended effect of making readers more willing to share unlabeled stories — even if those turn out to be untrue as well. Still, other surveys have suggested that in search, when websites are rated as containing unreliable information, the majority of people are less likely to share news from those sites. The impact Facebook, Twitter and YouTube's labels have had over these last few days, however, remains a mystery.

"There's been no research on the effectiveness of this," said Aimee Rinehart, U.S. deputy director of the misinformation project First Draft News.

As election results came in Tuesday and Wednesday, researchers applauded Twitter's strategy — particularly the most heavy-handed labels from the social media platform, which require users to click through an interstitial and prevent them from sharing or engaging with the post.

"Twitter's been the fastest to actually append effective labels and to actually hide objectionable content," said Emerson Brooking, a resident fellow at the Atlantic Council's Digital Forensic Research Lab.

The company took forceful action against tweets from President Trump falsely claiming Democrats were trying to "STEAL the election," hiding it behind a label that said some of the content in the post was "disputed and might be misleading about an election or other civic process."

Facebook's approach has, meanwhile, received more middling reviews. It also labeled President Trump's posts about election stealing, but those labels appeared beneath the post and did not limit users from sharing or engaging with the underlying message. "Final results may be different from initial vote counts," Facebook's label reads. Facebook has also begun applying the same label to all posts from both Biden and Trump, despite the fact that only the Trump campaign has prematurely declared victory, leading some to wonder whether the labels might confuse Facebook users about who's telling the truth.

Researchers have expressed similar concerns about YouTube, which has affixed small, subtle "information panels" with factual information directly under videos and search results related to the election, an approach that experts said could confuse people trying to differentiate between misinformation and reputable news sources. "Too often, YouTube has tried to get away with doing the minimum, and this is another instance of that," said Paul Barrett, deputy director of the New York University Stern Center for Business and Human Rights.

YouTube spokesperson Ivy Choi said in a statement that YouTube "remains vigilant with regards to election-related content in this post-election period."

"In this post-election period, our teams are continuing to work around the clock to quickly remove content misleading people about voting or encouraging interference in the democratic process, raise up authoritative news publishers in search results and 'watch next' panels, and reduce the spread of harmful election-related misinformation," Choi said. "On Election Day, we removed several livestreams for violating our spam policies, and our election results information panel is prominently surfaced above search results and under videos about the election."

Nina Jankowicz, a disinformation fellow at the Wilson Center, said Twitter's labels are likely the most effective because they provide "friction," requiring users to click through warnings with relevant context about why the posts are inaccurate. That process can slow people down and force them to reconsider what they're interacting with.

But Twitter has mainly reserved such muscular actions for the president's tweets. When Trump aides, including White House press secretary Kayleigh McEnany and Eric Trump, prematurely declared Trump had won Pennsylvania on Wednesday afternoon, Twitter affixed a less aggressive label underneath their posts. "Official sources may not have called the race when this was tweeted," the Twitter label reads.

"As votes are still being counted across the country, our teams continue to take enforcement action on tweets that prematurely declare victory or contain misleading information about the election broadly," said a Twitter spokesperson. "Our teams continue to monitor tweets that attempt to spread misleading information about voting, accounts engaged in spammy behavior, and tweets that make premature or inaccurate claims about election results."

One key question is whether any of this is slowing the spread of misinformation. Researchers are doubtful. "The information we have so far regarding the effectiveness of labeling generally is it doesn't really reduce the spread of content," Brooking said.

Some of Trump's most devoted followers have started to copy and paste the tweets that Twitter hides, according to the Election Integrity Partnership, which created an even bigger mess for Twitter to deal with. As of last night, "some of them were cleaned up [and] some of them weren't," said Kate Starbird, a researcher with the EIP.

In some cases, groups like the Real Facebook Oversight Board, a collective of academics and activists focused on accountability at Facebook, reported that misinformation continued to go viral on multiple platforms, even after it got labeled. "#StopTheSteal went from Twitter and transferred over to Facebook with millions of views," said Shireen Mitchell, a member of the group and founder of Stop Online Violence Against Women, in a statement. "It was labeled as inaccurate but it was still spread. It's the perfect example of digital voter suppression."

Beyond the impact information labels have on the spread of those posts, there are even trickier questions to answer, like do the labels actually convince people not to believe the underlying message? Do the labels unintentionally create a sort of Streisand effect, driving people to the original posts purely because they have labels? How much can a single misinformation label really accomplish now when, for four years, the president has been using social media to seed the idea that voter fraud is rampant in America, entirely without objection from Facebook or Twitter? By Election Day, was it already too late?

Getting to those answers would require more sophisticated polling of social media users, which so far, doesn't exist.

On Facebook, at least, that could change. Earlier this year, Facebook announced it would be working with a 17-person independent team of researchers to study the platform's impact on the 2020 election. Among the areas of study was the role Facebook plays in the spread of political misinformation. But it's unclear if the researchers will specifically look at whether people are actually processing the labels in ways that limit the misinformation's spread or, at the very least, helps deter people from believing in the misinformation themselves. Neither Facebook nor the lead researchers on the project responded to Protocol's request for comment.

Of course, it's noteworthy that tech companies are making an effort on this front at all. It's more than they could say they did in 2016 when misinformation went entirely unchecked by every social platform. And there are limits to what these companies alone can do. On Wednesday, even as Facebook and Twitter tried to correct the record on the president's claims about election stealing, his campaign was sending the same message to voters by email — where no one could say he's wrong.

Update: This story was updated at 4:52 p.m. PT to include statements from Twitter and YouTube.

Fintech

Judge Zia Faruqui is trying to teach you crypto, one ‘SNL’ reference at a time

His decisions on major cryptocurrency cases have quoted "The Big Lebowski," "SNL," and "Dr. Strangelove." That’s because he wants you — yes, you — to read them.

The ways Zia Faruqui (right) has weighed on cases that have come before him can give lawyers clues as to what legal frameworks will pass muster.

Photo: Carolyn Van Houten/The Washington Post via Getty Images

“Cryptocurrency and related software analytics tools are ‘The wave of the future, Dude. One hundred percent electronic.’”

That’s not a quote from "The Big Lebowski" — at least, not directly. It’s a quote from a Washington, D.C., district court memorandum opinion on the role cryptocurrency analytics tools can play in government investigations. The author is Magistrate Judge Zia Faruqui.

Keep Reading Show less
Veronica Irwin

Veronica Irwin (@vronirwin) is a San Francisco-based reporter at Protocol covering fintech. Previously she was at the San Francisco Examiner, covering tech from a hyper-local angle. Before that, her byline was featured in SF Weekly, The Nation, Techworker, Ms. Magazine and The Frisc.

The financial technology transformation is driving competition, creating consumer choice, and shaping the future of finance. Hear from seven fintech leaders who are reshaping the future of finance, and join the inaugural Financial Technology Association Fintech Summit to learn more .

Keep Reading Show less
FTA
The Financial Technology Association (FTA) represents industry leaders shaping the future of finance. We champion the power of technology-centered financial services and advocate for the modernization of financial regulation to support inclusion and responsible innovation.
Enterprise

AWS CEO: The cloud isn’t just about technology

As AWS preps for its annual re:Invent conference, Adam Selipsky talks product strategy, support for hybrid environments, and the value of the cloud in uncertain economic times.

Photo: Noah Berger/Getty Images for Amazon Web Services

AWS is gearing up for re:Invent, its annual cloud computing conference where announcements this year are expected to focus on its end-to-end data strategy and delivering new industry-specific services.

It will be the second re:Invent with CEO Adam Selipsky as leader of the industry’s largest cloud provider after his return last year to AWS from data visualization company Tableau Software.

Keep Reading Show less
Donna Goodison

Donna Goodison ( @dgoodison ) is Protocol's senior reporter focusing on enterprise infrastructure technology, from the 'Big 3' cloud computing providers to data centers. She previously covered the public cloud at CRN after 15 years as a business reporter for the Boston Herald. Based in Massachusetts, she also has worked as a Boston Globe freelancer, business reporter at the Boston Business Journal and real estate reporter at Banker & Tradesman after toiling at weekly newspapers.

Image: Protocol

We launched Protocol in February 2020 to cover the evolving power center of tech. It is with deep sadness that just under three years later, we are winding down the publication.

As of today, we will not publish any more stories. All of our newsletters, apart from our flagship, Source Code, will no longer be sent. Source Code will be published and sent for the next few weeks, but it will also close down in December.

Keep Reading Show less
Bennett Richardson

Bennett Richardson ( @bennettrich ) is the president of Protocol. Prior to joining Protocol in 2019, Bennett was executive director of global strategic partnerships at POLITICO, where he led strategic growth efforts including POLITICO's European expansion in Brussels and POLITICO's creative agency POLITICO Focus during his six years with the company. Prior to POLITICO, Bennett was co-founder and CMO of Hinge, the mobile dating company recently acquired by Match Group. Bennett began his career in digital and social brand marketing working with major brands across tech, energy, and health care at leading marketing and communications agencies including Edelman and GMMB. Bennett is originally from Portland, Maine, and received his bachelor's degree from Colgate University.

Enterprise

Why large enterprises struggle to find suitable platforms for MLops

As companies expand their use of AI beyond running just a few machine learning models, and as larger enterprises go from deploying hundreds of models to thousands and even millions of models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

As companies expand their use of AI beyond running just a few machine learning models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

Photo: artpartner-images via Getty Images

On any given day, Lily AI runs hundreds of machine learning models using computer vision and natural language processing that are customized for its retail and ecommerce clients to make website product recommendations, forecast demand, and plan merchandising. But this spring when the company was in the market for a machine learning operations platform to manage its expanding model roster, it wasn’t easy to find a suitable off-the-shelf system that could handle such a large number of models in deployment while also meeting other criteria.

Some MLops platforms are not well-suited for maintaining even more than 10 machine learning models when it comes to keeping track of data, navigating their user interfaces, or reporting capabilities, Matthew Nokleby, machine learning manager for Lily AI’s product intelligence team, told Protocol earlier this year. “The duct tape starts to show,” he said.

Keep Reading Show less
Kate Kaye

Kate Kaye is an award-winning multimedia reporter digging deep and telling print, digital and audio stories. She covers AI and data for Protocol. Her reporting on AI and tech ethics issues has been published in OneZero, Fast Company, MIT Technology Review, CityLab, Ad Age and Digiday and heard on NPR. Kate is the creator of RedTailMedia.org and is the author of "Campaign '08: A Turning Point for Digital Media," a book about how the 2008 presidential campaigns used digital media and data.

Latest Stories
Bulletins