Skip to Content

Here’s how social-media firms should tackle online hate, according to physics

Policing online hate groups is like a never-ending game of whack-a-mole, and it’s not working. Here are some ideas that might.
August 22, 2019
Inside Facebook's war room, where it monitors content
Inside Facebook's war room, where it monitors contentAP

Policing online hate groups is like a never-ending game of whack-a-mole: moderators remove one neo-Nazi page on Facebook, only for another to appear hours later. It’s an approach that isn’t working, but a team of physicists have used a study of networks to suggest several alternative strategies that might.

The scale of the problem: The team from George Washington University examined the dynamics of “hate communities”—groups that organize individuals with similar views—on social-media platforms Facebook and VKontakte (the equivalent in Russia) over a few months. They found that these networks are remarkably globally interconnected and resilient at the micro level when attacked, crossing platforms and jumping between countries, continents, and languages. Real-world evidence of this interconnectedness can be seen in the way white extremist attackers in Norway, New Zealand, and the US have explicitly drawn inspiration from each other.

The current approach is broken: The researchers’ mathematical model predicts that policing within a single platform, like Facebook, can actually make the spread of hate speech worse and could eventually push it underground, where it’s even harder to study and combat. The team explained their findings in a paper in Nature this week.

What can be done? The researchers suggest policies that could be implemented by social media companies:

— Ban relatively small hate clusters, rather than the largest. These are easier to locate, and eliminating them can help stop the larger clusters from forming in the first place.

— Ban a small number of users chosen randomly from online hate clusters. This avoids banning whole groups of users, which results in outrage and allegations of speech suppression.

— Encourage clusters of “anti-hate” users to form; they can counteract hate clusters.

— Since many hate groups online have opposing views, platform administrators should introduce an artificial group of users to sow division between these groups. The researchers found that these sorts of battles could bring down large hate clusters that have opposing views.

How likely is it? Some of the policies, especially the latter two, are pretty radical. But since current approaches are so profoundly ineffective, it’s surely worthwhile for social-media companies to try them out.  Over to you, Mark Zuckerberg.

Sign up here for our daily newsletter The Download to get your dose of the latest must-read news from the world of emerging tech.

Deep Dive


What’s next for AI regulation in 2024? 

The coming year is going to see the first sweeping AI laws enter into force, with global efforts to hold tech companies accountable. 

Three technology trends shaping 2024’s elections

The biggest story of this year will be elections in the US and all around the globe

Four lessons from 2023 that tell us where AI regulation is going

What we should expect in the coming 12 months in AI policy

The FTC’s unprecedented move against data brokers, explained

It could signal more aggressive action from policy makers to curb the corrosive effects that data brokers have on personal privacy.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at with a list of newsletters you’d like to receive.