ORA (Round 5) Towards realistic computational models of social influence dynamics

ORA（第 5 轮）迈向社会影响力动态的现实计算模型

• 批准号: ES/S015159/1
• 负责人: Bruce Edmonds
• 金额: $ 38.58万
• 依托单位: Manchester Metropolitan University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ES%2FS015159%2F1
• 关键词: ORA; Round; Towards; realistic; computational

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，许多社会转向了观点上的两极分化和波动性，例如在对移民或气候政策的态度方面，但理解的根本原因是很少的。一个关键的障碍是，社会中的意见动态涉及社会影响力的基本人际关系过程，网络结构（例如网络结构）和宏观成果（例如意见分布中的两极分化）之间的复杂微麦克罗相互作用。基于代理的仿真模型（ABM）提供了强大的工具，可以弥合理论上的微观流程和宏观级别的动态。但是，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。两个主要的障碍是1）缺乏各种模型的理论整合以及2）缺乏模型假设和预测的经验测试。 Torealsim是ABM领先专家和经验研究的一项独特的努力，以克服这两个障碍。结合了关于突出建模方法的专业知识，我们开发了一个系统地比较模型及其预测的框架。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，一种混合​​方法将模型与经验证据联系起来。我们从微观的假设和宏观预测方面进行了经验测试模型，提出了新一代的社会影响模型，该模型综合了Torealsim的见解。

项目成果

Why questions like 'do networks matter?' matter to methodology: how Agent-Based Modelling makes it possible to answer them

• DOI: 10.1080/13645579.2020.1801602
• 发表时间: 2020-07-31
• 期刊: INTERNATIONAL JOURNAL OF SOCIAL RESEARCH METHODOLOGY
• 影响因子: 3.3
• 作者: Chattoe-Brown, Edmund

The Role of Homophily in Opinion Dynamics: A Short Overview

同质性在舆论动态中的作用：简短概述

• 发表时间: 2020
• 作者: E. Chattoe-Brown

Socio-Cognitive Systems - A Position Statement

社会认知系统 - 立场声明

• 发表时间: 2022
• 作者: Dignum F

Is agent-based modelling the future of prediction?

基于代理的建模是预测的未来吗？

• DOI: 10.1080/13645579.2022.2137923
• 发表时间: 2022
• 期刊: International Journal of Social Research Methodology
• 影响因子: 3.3
• 作者: Chattoe-Brown E

Advances in Social Simulation - Proceedings of the 16th Social Simulation Conference, 20-24 September 2021

社会模拟的进展 - 第 16 届社会模拟会议论文集，2021 年 9 月 20-24 日

• DOI: 10.1007/978-3-030-92843-8_28
• 发表时间: 2022
• 作者: Bithell M