Modeling and Analyzing User Behavior and Decision-Making in Social Networks
社会网络环境下的决策建模与行为分析

陈玉旺 教授（曼彻斯特大学）

报告摘要：The rapid spread of information in today’s digital ecosystem has profoundly reshaped how individuals communicate, update beliefs, and make decisions. Social media platforms enable large-scale dissemination that supports coordination and collective action, yet they also create vulnerabilities to misleading, low-quality, and adversarial information. These dynamics can trigger serious societal consequences, including political polarization, economic disruption, and public health risks. This raises a critical challenge: how can decision-makers act responsibly and effectively in large-scale, uncertain, heterogeneous, and dynamic networked systems? This work addresses this challenge by developing data-driven, explainable, and uncertainty-aware modelling and analytics for information propagation and decision-making in social networks. The work aims to strengthen both decision theory and practice by providing decision-relevant outputs that can support prompt and resource-constrained interventions for platforms, organizations, and public-sector stakeholders.

报告人简介：陈玉旺，英国曼彻斯特大学教授，人工智能与决策科学研究中心联合主任。2008年于上海交通大学控制科学与工程专业获工学博士学位，2021年至2023年兼任阿兰·图灵研究所Turing Fellow。主要从事智能推理与决策、数据科学和系统科学等相关领域的理论和应用研究。近年来作为项目负责人或主要完成人承担完成Innovate UK, EPSRC, NSFC等资助的科研项目十余项。并在EJOR, JORS, Omega, DSS, IS, IEEE T-SMC等期刊和国际会议上发表了学术论文100多篇。