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

影响力、信息和病毒的传播等传染过程会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，以减轻大规模的传染，包括传染病大流行和错误的宣传运动。该项目还可以对国家安全产生积极影响，因为它使人们更好地了解社会影响在塑造公众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。研究人员团队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，并将包括对K-12学生和教师的广泛宣传。该项目旨在开发建模、分析和控制简单（例如，信息和疾病的传播）和复杂的传染（例如，影响力和意见的传播）。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。利用这个模型，研究小组将i）得出网络拓扑结构之间的基本关系，意见之间的相关性，以及传播动力学，包括支持每个意见的个人的最终分数; ii）揭示相关意见传播对人口极化的影响;以及iii）开发算法以在对其他意见和/或极化进行约束的情况下有效地控制意见的传播。对于简单的传染病，研究小组将分析信息和病毒传播的新模型，并揭示i）传播项目中的突变的影响; ii）人群中的异质性，例如，该奖项反映了NSF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.