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基于主体模型中观点与社会动态的共同演化网络

Co-evolving networks for opinion and social dynamics in agent-based models.

作者信息

Djurdjevac Conrad Nataša, Quang Vu Nhu, Nagel Sören

机构信息

Zuse Institute Berlin, 14195 Berlin, Germany.

Department of Mathematics and Computer Science, Institute of Computer Science, Freie Universität Berlin, 14195 Berlin, Germany.

出版信息

Chaos. 2024 Sep 1;34(9). doi: 10.1063/5.0226054.

Abstract

The rise of digital social media has strengthened the coevolution of public opinions and social interactions that shape social structures and collective outcomes in increasingly complex ways. The existing literature often explores this interplay as a one-directional influence, focusing on how opinions determine social ties within adaptive networks. However, this perspective overlooks the intrinsic dynamics driving social interactions, which can significantly influence how opinions form and evolve. In this work, we address this gap, by introducing the co-evolving opinion and social dynamics using stochastic agent-based models. Agents' mobility in a social space is governed by both their social and opinion similarity with others. Similarly, the dynamics of opinion formation is driven by the opinions of agents in their social vicinity. We analyze the underlying social and opinion interaction networks and explore the mechanisms influencing the appearance of emerging phenomena, such as echo chambers and opinion consensus. To illustrate the model's potential for real-world analysis, we apply it to General Social Survey data on political identity and public opinion regarding governmental issues. Our findings highlight the model's strength in capturing the coevolution of social connections and individual opinions over time.

摘要

数字社交媒体的兴起强化了公众舆论与社会互动的共同演化,这种演化以日益复杂的方式塑造着社会结构和集体结果。现有文献常常将这种相互作用视为一种单向影响,聚焦于观点如何在适应性网络中决定社会关系。然而,这种观点忽略了驱动社会互动的内在动态,而这种动态会显著影响观点的形成和演变。在这项工作中,我们通过使用基于随机主体的模型引入共同演化的观点和社会动态来填补这一空白。主体在社会空间中的移动受其与他人的社会和观点相似性的共同支配。同样,观点形成的动态由其社会邻域内主体的观点驱动。我们分析潜在的社会和观点互动网络,并探索影响新兴现象出现的机制,如回音室效应和观点共识。为了说明该模型在现实世界分析中的潜力,我们将其应用于关于政治身份和对政府问题的公众舆论的综合社会调查数据。我们的研究结果凸显了该模型在捕捉社会联系和个人观点随时间共同演化方面的优势。

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