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Preprint Study: 10 FIB Superspreaders Responsible for A Third of Twitter Misinformation [1]

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Date: 2022-07-25

A new preprint study, not yet peer reviewed but up on Arxiv for public review (commonplace for tech-world papers), finds that Twitter is letting major misinformation superspreaders pollute its platform. These superspreaders are largely conservative pundits and pseudo-media outlets, and they're much more toxic than even other average misinfo shitposters.

In a Twitter thread summarizing the findings , lead author Matt DeVerna explained that the team used "various metrics to predict whether an account will be a superspreader in future months and then see which ones perform the best. Then we do a qualitative review of the worst superspreaders we find and report what we learned."

To find the superspreaders, they created the False Information Broadcaster, or FIB index, based on things like how many followers an account hase and how much they get retweeted, and then "finds the worst misinfo spreaders who consistently share low-credibility content." That's really key to the FIB index's power, the study explains, because it's identifying people who aren't accidentally sharing something that's wrong once or twice, amongst lots of other content. It's accounts that are repeatedly sharing misleading content, day after day, like it's their job.

And it turns out, to the surprise of no one who's been paying attention, it is! Not only are many of the superspreaders blue-check verified, but also they found "pundits with large followings, low-credibility media outlets, personal accounts affiliated with those media outlets, and a range of less popular influencers. Most (not all) are conservative." (Per the paper, 91% of the political accounts were conservative, so "these results agree with literature that finds an asymmetric tendency for conservative users to share misinformation online compared to liberal users.")

Of the misinformation-spreading accounts identified, the "analysis found that 10 superspreaders (0.003% of accounts) were responsible for originating over 34% of the misinformation shared during the eight months that followed their identification, and 1,000 accounts (0.25%) were responsible for more than 70%!"

How are those 10 superspreaders so effective? Part of it is that they're particularly nasty, as the research found that "superspreaders utilize more toxic language than the average misinformation sharer on Twitter." So not only would taking away their twitter megaphone make the site less lie-packed, it would also make it less toxic.

And while many of the accounts in the dataset used have since been banned, DeVerna said the "analysis also suggests that Twitter may be more lenient with prominent superspreaders. Of the superspreaders who were suspended, less than 3% were verified and less than 10% had more than 150k followers."

Which leads to one of the researchers' "key concerns: The more prominent misinformation superspreaders become, the greater their negative impact will be, and the more difficult they become to reign in."

Turning to the study itself, a few fun highlights. To produce the FIB index, one of the tools the researchers evaluated was BotScore, the extent to which the account may be a bot. But that actually " performs the worst: even after more than 2,000 accounts are removed from the network, most of the misinformation still remains in the net- work. This suggests that bots infrequently originate the misinformation on Twitter." Bots may amplify someone's lies, but they're mostly a distraction.

And while the paper doesn't seem to explicitly list the top 10 superspreaders they identified, they do name a few, like pro-climate but anti-vaxx Robert Kennedy Jr, "one of the top superspreaders of COVID-19 vaccine disinformation.

Then there's a regular fixture in this space , "Steve Milloy, who has been labeled a 'pundit for hire' for the oil and tobacco industries".

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[1] Url: https://www.dailykos.com/stories/2022/7/25/2112463/-Preprint-Study-10-FIB-Superspreaders-Responsible-for-A-Third-of-Twitter-Misinformation

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