科学研究

活动主题：Structure and Dynamics of Information Spreading in Networked Systems

活动类型：学术交流

举办单位：智慧民航科创中心

活动时间：2025-09-11日 10:00-11:30

活动地点：会议中心1014

面向群体：全院师生

主讲嘉宾：

Prof. Yamir Moreno currently serves as the Director of the Institute for Biocomputation and Physics of Complex Systems (BIFI) and the Head of the Complex Systems and Networks Lab (COSNET) at the University of Zaragoza, while also holding the position of Professor of Physics in the Department of Theoretical Physics, Faculty of Sciences at the same university. He was elected a Fellow of the American Physical Society in 2021 and the Network Science Society in 2022. From 2022 to 2024, he worked as the Research Director, Principal Scientist, and Chair of the Steering Committee at the CENTAI Institute (Center for Artificial Intelligence) in Turin, Italy, and he also served as the elected President of the Network Science Society from 2018 to 2022. Prof. Moreno's research focuses on the theoretical foundations of complex systems, which he explores mainly using tools from mathematics, physics, and network science; his research interests include disease dynamics, diffusion processes, human behavior, mathematical biology, nonlinear dynamical processes, and the structure and dynamics of complex systems. As of May 2025 (with data sources indicated), he has published over 290 scientific papers—according to Google Scholar, his papers have received more than 55,300 citations with an h-index of 87, and according to Web of Science, his total citations exceed 33,500 with an h-index of 73.

内容摘要：

The global challenge of misinformation is now recognized as a major societal risk, with large-scale group-based messaging platforms playing a central role in how information circulates. Despite this, most mathematical models of rumor dynamics are still grounded in pairwise interactions, leaving the complex reality of group-level communication largely unexplored. In this talk, we first review some previous approaches to deal with the problem of characterizing the structure and dynamics of information dissemination at different scales. We then turn our attention to introducing a new higher-order rumor model on hypergraphs, embedding a group-based annihilation mechanism that mirrors the way people disengage from spreading information once enough members of their groups are informed. We report two distinct ways rumors can fade away: an exponential decay, where interest dies quickly, and a power-law decay, where the process slows and lingers. We find that both can coexist in the same system, depending on network structure and starting conditions. By linking theory to real-world data, our work opens new avenues for studying how information —true or false— spreads in modern, group-based communication networks. This could inform better strategies to manage misinformation, and future research could explore other forms of group-based stopping behavior or test the model in controlled experiments.

联系人：智慧民航科创中心，路丹

编辑：袁晓慧