Al Jazeera
At least 20 states have passed regulations against election deepfakes, but federal action remains stalled.
How can physics help solve real world problems? – NEIL JOHNSON, Head of Dynamic Online Networks Lab
Education, The Creative Process Podcast
How can physics help solve messy, real world problems? How can we embrace the possibilities of AI while limiting existential risk and abuse by bad actors?
Neil Johnson is a physics professor at George Washington University. His new initiative in Complexity and Data Science at the Dynamic Online Networks Lab combines cross-disciplinary fundamental research with data science to attack complex real-world problems. His research interests lie in the broad area of Complex Systems and ‘many-body’ out-of-equilibrium systems of collections of objects, ranging from crowds of particles to crowds of people and from environments as distinct as quantum information processing in nanostructures to the online world of collective behavior on social media.
Online hate stems from small platforms, researchers find
GW Hatchet
Researchers found online hate develops on smaller social media platforms instead of mainstream ones in a study published earlier this month.
Nonlinear spreading behavior across multi-platform social media universe
Chaos: An Interdisciplinary Journal of Nonlinear Science
Understanding how harmful content (mis/disinformation, hate, etc.) manages to spread among online communities within and across social media platforms represents an urgent societal challenge. We develop a non-linear dynamical model for such viral spreading, which accounts for the fact that online communities dynamically interconnect across multiple social media platforms. Our mean-field theory (Effective Medium Theory) compares well to detailed numerical simulations and provides a specific analytic condition for the onset of outbreaks (i.e., system-wide spreading). Even if the infection rate is significantly lower than the recovery rate, it predicts system-wide spreading if online communities create links between them at high rates and the loss of such links (e.g., due to moderator pressure) is low. Policymakers should, therefore, account for these multi-community dynamics when shaping policies against system-wide spreading.
Shockwaves Link (Anti)Social Behavior Across the Internet
Springer-Nature “Behind the Paper”
A first-of-its kind network map of the online hate ecosystem provides new insight into decentralized behavior during January 6, 2021, and its implications for 2024 and beyond
Online Hate Thrives and Survives on Smaller Social Media Platforms, Study Finds
GW Press Office
New research published today in the journal npj Complexity shows that online hate thrives because of a hidden inner web of many small social media platforms – not the few large platforms such as Twitter (X) and Facebook (Meta).
Softening Online Extremes Using Network Engineering
Elliott School Press Office
In her latest article, “Softening Online Extremes Using Network Engineering,” Elliott School Associate Professor Elvira-Maria Restrepo and her co-authors Martin Moreno, Lucia Illari, and Neil F. Johnson offer solutions for mitigating dangerous misinformation and extreme views online.
Adaptive link dynamics drive online hate networks and their mainstream influence
NPJ Complexity
Online hate is dynamic, adaptive— and may soon surge with new AI/GPT tools. Establishing how hate operates at scale is key to overcoming it. We provide insights that challenge existing policies. Rather than large social media platforms being the key drivers, waves of adaptive links across smaller platforms connect the hate user base over time, fortifying hate networks, bypassing mitigations, and extending their direct influence into the massive neighboring mainstream. Data indicates that hundreds of thousands of people globally, including children, have been exposed. We present governing equations derived from first principles and a tipping-point condition predicting future surges in content transmission. Using the U.S. Capitol attack and a 2023 mass shooting as case studies, our findings offer actionable insights and quantitative predictions down to the hourly scale. The efficacy of proposed mitigations can now be predicted using these equations.
Minzhang Zheng, Richard Sear, Lucia Illari, Nicholas Restrepo, Neil Johnson
Softening online extremes using network engineering
IEEE Access
The prevalence of dangerous misinformation and extreme views online has intensified since the onset of Israel-Hamas war on 7 October 2023. Social media platforms have long grappled with the challenge of providing effective mitigation schemes that can scale to the 5 billion-strong online population. Here, we introduce a novel solution grounded in online network engineering and demonstrate its potential through small pilot studies. We begin by outlining the characteristics of the online social network infrastructure that have rendered previous approaches to mitigating extremes ineffective. We then present our new online engineering scheme and explain how it circumvents these issues. The efficacy of this scheme is demonstrated through a pilot empirical study, which reveals that automatically assembling groups of users online with diverse opinions, guided by a map of the online social media infrastructure, and facilitating their anonymous interactions, can lead to a softening of extreme views. We then employ computer simulations to explore the potential for implementing this scheme online at scale and in an automated manner, without necessitating the contentious removal of specific communities, imposing censorship, relying on preventative messaging, or requiring consensus within the online groups. These pilot studies provide preliminary insights into the effectiveness and feasibility of this approach in online social media settings.
Predicting and Controlling Bad Actor Artificial Intelligence
Templeton Ideas
In an era of super-accelerated technological advancement, the specter of malevolent artificial intelligence (AI) looms large. While AI holds promise for transforming industries and enhancing human life, the potential for abuse poses significant societal risks. Threats include avalanches of misinformation, deepfake videos, voice mimicry, sophisticated phishing scams, inflammatory ethnic and religious rhetoric, and autonomous weapons that make life-and-death decisions without human intervention.