面对内在个体偏差时对真假信息的双重传播建模
Modeling Duelling Contagions of True and False Information in the Face of Inherent Individual biases
AI总结：
研究面对真假信息双重传播及个体偏差的问题，提出基于“复杂传播”和“沉默螺旋”理论的主体共同传播模型，发现早期传播者持有的操纵性叙述会主导，早期播种低自我审查主体可限制操纵传播并使明智人群占优，为相关政策提供启示。
AI中文摘要：
先进的数字通信彻底改变了人们创造和消费信息的方式，使信息传播成为从公共卫生到国家安全等领域的重要研究课题。现实世界中的信息传播场景通常涉及相互竞争的叙述——真实的和虚假的——同时传播。我们提出了一种基于“复杂传播”和“沉默螺旋”理论的新型基于主体的共同传播模型，以捕捉网络动态如何利用认知偏差来塑造这种互动。我们的研究结果表明，当早期传播者持有操纵性叙述时，它们会占据主导地位。这些网络动态进一步利用内在认知偏差来放大信息传播，而不管其真实性如何。此外，虽然有利的先前经验会增强集体乐观情绪，但不利的经验只会适度削弱乐观情绪。然而，我们发现，对自我审查较低的主体进行早期播种不仅可以限制操纵的传播，还可以导致明智人群的主导地位。这对旨在促进更健康的话语、加强社会凝聚力和确保公平获取可靠信息的政策具有启示意义。
英文摘要：
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.
