GW Today
As the election approaches, GW researchers detailed how major events strengthen global hate networks online and incite new content around hot-button issues.
How a U.S. election strengthened the global hate network
Springer-Nature “Behind the Paper”
The most detailed mapping of structure and content across the multi-platform online world reveals how the most recent U.S. presidential election reinforced online hate and extremism
How U.S. Presidential elections strengthen global hate networks
NPJ Complexity
Local or national politics can be a catalyst for potentially dangerous hate speech. But with a third of the world’s population eligible to vote in 2024 elections, we need an understanding of how individual-level hate multiplies up to the collective global scale. We show, based on the most recent U.S. presidential election, that offline events are associated with rapid adaptations of the global online hate universe that strengthens both its network-of-networks structure and the types of hate content that it collectively produces. Approximately 50 million accounts in hate communities are drawn closer to each other and to a broad mainstream of billions. The election triggered new hate content at scale around immigration, ethnicity, and antisemitism that aligns with conspiracy theories about Jewish-led replacement. Telegram acts as a key hardening agent; yet, it is overlooked by U.S. Congressional hearings and new E.U. legislation. Because the hate universe has remained robust since 2020, anti-hate messaging surrounding global events (e.g., upcoming elections or the war in Gaza) should pivot to blending multiple hate types while targeting previously untouched social media structures.
Presidential Elections Unite Online Hate Groups
Mirage News
A new study published today details the ways in which the 2020 U.S. election not only incited new hate content in online communities but also how it brought those communities closer together around online hate speech.
U.S. officials sound alarm about election misinformation
DC News Now
U.S. officials are sounding the alarm over election misinformation online. They’re warning of foreign actors trying to sow discord with fake videos and images.
Prior work shows same main takeaway
Science eLetters
This short eLetter shows that our earlier published studies precede the recently claimed breakthrough in use of automated/software/AI-based deliberation to soften extremes of opinions.
Behind The Screen: How Bots Are Quietly Shaping The Digital World
Forbes
It began with just one post. Late one night, I was scrolling through my social media feed, and something caught my eye. You know that feeling when something doesn’t sit quite right, like an image in a puzzle that doesn’t fit.
Non-equilibrium physics of multi-species assembly applied to fibrils inhibition in biomolecular condensates and growth of online distrust
Scientific Reports
Self-assembly is a key process in living systems—from the microscopic biological level (e.g. assembly of proteins into fibrils within biomolecular condensates in a human cell) through to the macroscopic societal level (e.g. assembly of humans into common-interest communities across online social media platforms). The components in such systems (e.g. macromolecules, humans) are highly diverse, and so are the self-assembled structures that they form. However, there is no simple theory of how such structures assemble from a multi-species pool of components. Here we provide a very simple model which trades myriad chemical and human details for a transparent analysis, and yields results in good agreement with recent empirical data. It reveals a new inhibitory role for biomolecular condensates in the formation of dangerous amyloid fibrils, as well as a kinetic explanation of why so many diverse distrust movements are now emerging across social media. The nonlinear dependencies that we uncover suggest new real-world control strategies for such multi-species assembly.
Pedro Manrique, Frank Yingjie Huo, Sara El Oud, Neil Johnson
10 Predictions of Unknown Unknowns in Current and Future Conflicts
September 2024, DOD Basic Research Forum
Abstract: Human conflict will always appear chaotic and serve up unknown unknowns. But this talk shows how combining simple mechanistic representations of how fighters fight with state-of-the-art data, provides new insight into future unknown unknowns – and quantitative predictions. Examples include the Israel-Palestine region, Russia-Ukraine and also future ‘Total War’ scenarios in which cyber-terrorism and malicious AI use will play a role. The predictions range from future casualties to unexpected technological advancements by an adversary; new and unanticipated tactics such as cyberattacks or biological warfare; sudden alliances or geopolitical shifts that alter the balance of power; and insurgencies or terrorist attacks in areas or by groups not previously considered a threat. This empirically-grounded mechanistic perspective on future warfare, threats, and total surprises, can inform future interventions, hidden shifts and casualty risk.
Bad Actor AI and Defending the Online Battlefield with Prof Neil Johnson
Paradigm Podcast
Neil Johnson is a professor of physics at George Washington University. He heads up the Dynamic Online Networks Lab, which combines modern data science with cross-disciplinary fundamental research to tackle problems such as the spread of online misinformation, and the impact of bad-actor generative AI tools in online battlefields.
Neil is a Fellow of the American Physical Society (APS), was former Research Fellow at the University of Cambridge, and Professor of Physics at the University of Oxford. His published books include Financial Market Complexity, and Simply Complexity: A Clear Guide to Complexity Theory.