Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, NM 87501, USA.
Complexity Science Hub Vienna, Austria.
J R Soc Interface. 2021 Mar;18(176):20200857. doi: 10.1098/rsif.2020.0857. Epub 2021 Mar 17.
Belief change and spread have been studied in many disciplines-from psychology, sociology, economics and philosophy, to biology, computer science and statistical physics-but we still do not have a firm grasp on why some beliefs change more easily and spread faster than others. To fully capture the complex social-cognitive system that gives rise to belief dynamics, we first review insights about structural components and processes of belief dynamics studied within different disciplines. We then outline a unifying quantitative framework that enables theoretical and empirical comparisons of different belief dynamic models. This framework uses a statistical physics formalism, grounded in cognitive and social theory, as well as empirical observations. We show how this framework can be used to integrate extant knowledge and develop a more comprehensive understanding of belief dynamics.
信念的改变和传播在许多学科中都有研究,包括心理学、社会学、经济学、哲学、生物学、计算机科学和统计物理学等,但我们仍然没有完全理解为什么有些信念更容易改变,传播得更快。为了全面捕捉产生信念动态的复杂社会认知系统,我们首先回顾了不同学科研究的信念动态的结构组成部分和过程的见解。然后,我们概述了一个统一的定量框架,该框架可用于对不同信念动态模型进行理论和经验比较。该框架使用基于认知和社会理论以及经验观察的统计物理形式。我们展示了如何使用该框架来整合现有知识并更全面地了解信念动态。