Elizabeth William

    • Information Futures Lab, School of Public Health, Brown University, Providence, Rhode Island

Physics 16, 89

A theory derived from nonlinear fluid dynamics is able to reproduce the dynamics of the formation of online hate communities, offering insights that could inform public policies.

APS/Charin Cain

Figure 1: Manrique and colleagues have developed a new theory whose predictions (solid line) match data on the dynamics of online “anti-X” communities (square symbols). The theory, derived from fluid dynamics, shows that the growth of these communities resembles the growth of non-linear waves in a liquid (drawn in the background).Manrique and colleagues have developed a new theory whose predictions (solid line) match data on the dynamics of online “anti-X” communities (square symbols). The theory, derived from fluid dynamics, shows that the growth of these communities is remi… Show more

The spread of harmful online content is becoming one of our society’s most pressing problems, a trend that the COVID-19 pandemic has significantly accelerated. Such content drives and amplifies dangerous behavior. In public health practice, for example, we have observed that online disinformation has impacted people’s trust in health authorities and measures including social distancing, masking recommendations, vaccines and treatments. Despite the urgency, a comprehensive description of the dynamics of online information, which would be essential to inform the formulation of public policies, is lacking. Now Pedro Manrique and colleagues at George Washington University in Washington, DC have addressed an important aspect of those dynamics [1] (Fig.1). They presented a “first principles” theory, derived from nonlinear fluid dynamics and nonequilibrium statistical physics, that captures the formation of online communities advocating “anti-X” hate. where X can denote categories related to religion, science, ethnicity, race, and other. The theory not only explains how harmful online activity develops, but also provides hints at how this development could be slowed or even prevented by regulating what researchers call collective online chemistry.

The COVID-19 pandemic has renewed interest in systematic approaches that take into account the risks associated with online information. Since 2020, initiatives led by the World Health Organization have brought together practitioners, policymakers and experts in scientific fields as diverse as law, behavioral sciences, digital health, user experience, information sciences and physics with the aim of leading the global ‘infodemiology’ research agenda. These initiatives have identified ways to assess the impact of misinformation on health, but have also suggested promising mitigation strategies, some of which have been screened in small-scale trials involving a few hundred to a few thousand online users. But the problem comes with a huge scale challenge: An estimated 5 billion people are online, and new users continue to add to that tally every day.

A new science that rigorously describes anti-X activity at the required scale must take into account the special characteristics of online dynamics. In online spaces, people don’t just exchange information, they interact with each other and form communities in support or opposition to certain shared tastes, values ​​or opinions. The formation dynamics of anti-X groups can be extremely complex. These groups can appear out of nowhere and grow very quickly, but also suddenly disappear when closed by moderators. Multiple groups can undergo “merger” and form larger groups, while “split” can lead some groups to split into smaller entities. Individuals and groups can also have “personalities” that evolve over time. Supported by a large set of empirical data, Manrique and colleagues have now provided a scientific description of these complex dynamics.

The researchers’ key insight is that online communities can be treated as a fluid. The correct description of boiling water comes not from considering the water molecules one at a time, but from taking into account the related pockets (bubbles) that the molecules form. Likewise, the proper science of how an online system “bubbles” relies on a proper description of related “user pockets,” i.e. online communities and how these communities interconnect. Building on this analogy, Manrique and collaborators apply nonlinear fluid dynamics to mathematically describe how collections of diverse individuals aggregate into communities, and how communities aggregate and evolve within Internet platforms or across multiple platforms. The intriguing picture that emerges from this model is that the characteristics of anti-X dynamics resemble those of shock waves in a fluid, those that can produce abrupt changes in macroscopic properties such as pressure, temperature or density.

While previous studies have addressed this problem, they have been unable to explain some of the complex features of these dynamical systems. In particular, they failed to capture the cumulative impact that the reverberation and amplification of information can have on people’s behaviors and online community formation. Even seemingly benign and irrelevant information can have dramatic effects due to the social dynamics it triggers, something the new theory successfully captures. Furthermore, the analytical description proposed by Manrique and collaborators can in principle address problems at any scale.

The researchers show remarkable agreement between their model’s predictions and a huge dataset they’ve been collecting since 2014, covering platforms ranging from Facebook to the Russian platform VK. Their formalism successfully reproduces, for example, the empirical form of the growth curves of pro-ISIS communities on VK and anti-government communities on Facebook related to the US Capitol uprising. In their model, a significant fraction of the total population can suddenly condense into one large cluster, a shock wave.

Importantly, the model shows that community dynamics can be controlled by acting on a parameter, called online collective chemistry, which quantifies the average probability of merging between different groups. This observation allowed the team to evaluate two general mitigation scenarios and to explain why in some cases removing individuals or organizations from online conversations or even entire communities from online platforms does not prevent them from reforming. These insights will be useful in informing approaches to addressing health misinformation in future emergencies.

The rigorous mathematical description of Manrique and colleagues, grounded in fluid dynamics and controlled by empirical data, offers a general model that could be applicable to a wide range of online threats. Similar approaches will become even more important in the future with the emergence of new online platforms and services, gaming technologies that parents cannot supervise and new artificial intelligence tools, from ChatGPT to content moderation and promotion algorithms , which will disrupt the information environment.

So just as we demand a solid scientific basis when discussing nuclear energy or climate science, we must do the same for online information problems that can have serious consequences for our society. The work by Manrique and colleagues is an encouraging step toward developing a scientific language that could describe these phenomena and guide science-based strategies to address them.


The author acknowledges the contributions of Tina D. Purnat, with the World Health Organization’s Department of Epidemic and Pandemic Preparedness and Prevention, to the conceptualization of this article.


  1. PD Manique et al.Shockwave-like behavior on social media, Phys. Rev. Lett. 130237401 (2023).

About the author

Image of Elizabeth William

Elisabeth Wilhelm is a Visiting Fellow at the Information Futures Lab at the Brown University School of Public Health. Since 2016, she has been dealing with national and global health disinformation and communication strategies related to vaccinations and health emergencies. She has worked for the US Centers for Disease Control and Prevention, UNICEF and the US Agency for International Development. During the COVID-19 pandemic she has worked to advance the field of infodemic management and infodemiology, working internationally with collaborators from the World Health Organization, academia and the public health sector.

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