CIF: Small: Modeling, Analysis, and Control of Contagion Processes in Networks

CIF：小型：网络中传染过程的建模、分析和控制

基本信息

批准号：
2225513
负责人：
Osman Yagan
金额：
$ 60万
依托单位：
Carnegie-Mellon University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-10-01 至 2025-09-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2225513&HistoricalAwards=false
关键词：
CIF Small Modeling Analysis Control

项目摘要

Contagion processes such as propagation of influence, information, and viruses can have dramatic impacts on the health and well-being of the society. This project will reveal how contagions are affected by various factors and parameters, some of which can be controlled by public-policy measures and by adjusting individuals’ behaviors. Thus, the project can help in developing efficient mechanisms for mitigating large-scale contagions including infectious-disease pandemics and misinformation campaigns. The project can also have a positive impact on national security by providing an improved understanding of the role of social influence in shaping popular opinion and actions, and thereby an improved capability to predict and control spread of antisocial behavior. The team of researchers will incorporate project results in teaching and disseminate them broadly in academic and industrial venues. The project will involve women and minority students and will include extensive outreach to K-12 students and teachers. This project aims to develop new approaches in modeling, analysis, and control of simple (e.g., spread of information and diseases) and complex contagions (e.g., spread of influence and opinions) over networks. First, a novel complex contagion model will be used to study the simultaneous spread of multiple correlated opinions. Utilizing this model, the team of researchers will i) derive fundamental relations between the network topology, the correlations among opinions, and the propagation dynamics including final fraction of individuals supporting each opinion; ii) reveal the impact of correlated opinion propagation on the polarization in the population; and iii) develop algorithms to efficiently control the spread of an opinion with constraints on other opinions and/or polarization. For simple contagions, the team of researchers will analyze novel models of both information and viral spread and reveal the impact of i) mutations in the spreading item; and ii) the heterogeneity in the population, e.g., due to different mask-wearing behavior, vaccination status, or socio-cultural diversity, on the contagion dynamics.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

影响、信息和病毒的传播等传染过程可能对社会的健康和福祉产生巨大影响。该项目将揭示各种因素和参数如何影响传染，其中一些因素和参数可以由公众控制。因此，该项目可以帮助制定有效的机制，以减轻大规模传染病，包括传染病大流行和错误信息宣传活动，通过提供更好的理解，对国家安全产生积极影响。角色的研究人员团队将在学术和工业场所广泛传播项目成果，从而提高预测和控制反社会行为蔓延的能力。该项目旨在开发对简单传染病（例如信息和疾病的传播）和复杂传染病（例如影响力和疾病的传播）进行建模、分析和控制的新方法。意见）通过网络。首先，将使用一种新颖的复杂传染模型来研究多个相关意见的同时传播，研究人员团队将i）得出网络拓扑、意见之间的相关性以及包括最终在内的传播动态之间的基本关系。支持每种观点的个人比例；ii) 揭示相关观点传播对群体极化的影响；以及 iii) 开发算法以在限制其他观点和/或极化的情况下有效控制观点的传播。团队的研究人员将分析信息和病毒传播的新模型，并揭示 i) 传播项目突变的影响；以及 ii) 人群的异质性，例如，由于不同的口罩佩戴行为、疫苗接种状况或社会地位该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。