ToRealSim Towards realistic computational models of social influence dynamics

ToRealSim 迈向社会影响动态的现实计算模型

• 批准号: 396901899
• 负责人: Professor Dr. Klaus Boehnke
• 金额: --
• 依托单位: Complex Systems Lab (LISC)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2022-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/396901899?language=en
• 关键词: ToRealSim; Towards; realistic; computational; models

Recently, many societies shifted towards more polarization and volatility in opinions, for example in attitudes about immigration or climate policy, but underlying reasons are poorly understood. A key obstacle is that opinion dynamics in society involve a complex micro-macro interaction between fundamental interpersonal processes of social influence, meso-level conditions like network structures, and macro-level outcomes, like polarization in opinion distributions. Agent-based simulation models (ABM) offer powerful tools to bridge theoretically micro-level processes and macro-level dynamics. However, ABM of social influence hitherto fails to inform empirical research and policy. Two major roadblocks are 1) a lack of theoretical integration of the large variety of models and 2) a lack of empirical tests of model assumptions and predictions. ToRealSim is a unique effort by a consortium of leading experts in ABM and empirical research to overcome both roadblocks. Combining expertise on prominent modelling approaches, we develop a framework to systematically compare models and their predictions. Drawing on this, a mixed-method approach will link models to empirical evidence, utilizing our expertise on qualitative research, experiments, social network analysis and survey research. We test models empirically, both in terms of micro-level assumptions and macro-level predictions, proposing a new generation of social influence models that synthesizes insights from ToRealSim.

最近，许多社会的观点变得更加两极分化和波动，例如对移民或气候政策的态度，但人们对根本原因知之甚少。一个关键障碍是，社会舆论动态涉及社会影响力的基本人际过程、网络结构等中观水平条件和舆论分布两极分化等宏观水平结果之间复杂的微观和宏观相互作用。基于代理的仿真模型（ABM）提供了强大的工具来连接理论上的微观过程和宏观动态。然而，迄今为止，社会影响力的 ABM 未能为实证研究和政策提供信息。两个主要障碍是：1）缺乏对各种模型的理论整合；2）缺乏对模型假设和预测的实证检验。 ToRealSim 是 ABM 和实证研究方面的领先专家组成的联盟为克服这两个障碍而做出的独特努力。结合重要建模方法的专业知识，我们开发了一个框架来系统地比较模型及其预测。以此为基础，混合方法将利用我们在定性研究、实验、社交网络分析和调查研究方面的专业知识，将模型与经验证据联系起来。我们从微观层面的假设和宏观层面的预测方面对模型进行实证测试，提出综合了 ToRealSim 见解的新一代社会影响力模型。