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

传染过程，如影响、信息和病毒的传播，可以对社会的健康和福祉产生巨大影响。该项目将揭示传染如何受到各种因素和参数的影响，其中一些因素和参数可以通过公共政策措施和调整个人行为来控制。因此，该项目可以帮助制定有效的机制，以减轻大规模传染，包括传染病大流行和虚假宣传运动。该项目还可以对国家安全产生积极影响，使人们更好地了解社会影响在形成舆论和行动方面的作用，从而提高预测和控制反社会行为蔓延的能力。研究小组将把项目成果纳入教学，并在学术和工业场所广泛传播。该项目将涉及妇女和少数民族学生，并将包括广泛接触K-12学生和教师。本项目旨在开发新的方法，对网络上简单的（如信息和疾病的传播）和复杂的传染（如影响和意见的传播）进行建模、分析和控制。首先，我们将使用一个新的复杂传染模型来研究多个相关意见的同时传播。利用该模型，研究团队将i)推导出网络拓扑、观点之间的相关性和传播动态之间的基本关系，包括支持每种观点的个体的最终比例；Ii)揭示相关舆论传播对人口两极分化的影响；iii)开发算法来有效地控制一种观点的传播，同时约束其他观点和/或两极分化。对于简单的传染，研究小组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；ii)人群的异质性，例如，由于不同的戴口罩行为、疫苗接种状况或社会文化多样性，对传染动态的影响。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.