Modeling Duelling Contagions of True and False Information in the Face of Inherent Individual biases
2026-07-27 • Social and Information Networks
Social and Information NetworksHuman-Computer Interaction
AI summaryⓘ
The authors created a computer model to study how true and false information spreads through social networks. They found that false or manipulative stories tend to take over if they start spreading early, because people’s biases help amplify all types of information. Positive past experiences make groups more optimistic, but bad experiences only slightly reduce this optimism. Interestingly, if people who speak up early are less likely to censor themselves, truthful information can spread more and reduce manipulation. This research helps think about ways to promote honest information and healthier conversations online.
information diffusionagent-based modelcomplex contagionspiral of silencecognitive biasesnetwork dynamicsself-censorshipmanipulative narrativessocial cohesionearly seeding
Authors
Vaibhav Krishna, Hirokazu Shirado, Feng Fu, Nicholas A. Christakis
Abstract
Advanced digital communication has revolutionized how people create and consume information, making information diffusion an important topic of research for domains from public health to national security. Real-world scenarios of information diffusion often involve competing narratives - true and false - spreading simultaneously. We propose a novel agent-based co-diffusion model, grounded in "complex-contagion" and "spiral of silence" theories, to capture how network dynamics exploit cognitive biases to shape such interactions. Our findings reveal that manipulative narratives dominate when early spreaders hold them. These network dynamics further exploit inherent cognitive biases to amplify information diffusion regardless of veracity. Further, while favourable previous experience strengthen collective optimism, unfavourable experiences attenuate optimism only modestly. However, we found that early seeding of agents with lower self-censorship not only constrains the spread of manipulation but can also lead to dominance of well-informed populance. This has implications for policies that aim to facilitate healthier discourse, strengthen social cohesion, and ensure equitable access to reliable information.