NetSE: Large: Collaborative Research: Contagion in large socio-communication networks

简单的传染过程是复杂网络中各种现象的基础，例如疾病在社会接触网络中的传播和信息在通信网络中的传播；了解它们的动态和开发控制机制是许多应用中的关键问题。本建议的目标是：(i)发展使用部分和噪声数据构建综合关系网络的方法；（ii）了解这些网络的结构和传染过程，特别是对传染动态有影响的重要网络特性和典型模式；发展技术以控制传染过程的蔓延，并发现、预防和制止社会-技术相互联系的网络中的一连串失败；（iv）理解网络和动态之间的共同进化，并利用这一点来完善他们的模型，以及控制它们的策略。这项工作的广泛影响包括在解决复杂网络中的基本问题方面弥合社会科学和计算机科学之间的差距，相应增强课程设置，以及各级学生的参与。

Simple contagion processes underlie various phenomena on complex networks, such as the spread of diseases on social-contact networks and information in communication networks; understanding their dynamics and developing control mechanisms are key issues in numerous applications. The goals of this proposal are: (i) Developing methods to construct synthetic relational networks using partial and noisy data; (ii) Understanding the structure of these networks and the contagion processes, and especially important network properties and typical patterns that have an impact on the dynamics of contagion; (iii) Developing techniques to control the spread of contagion processes, and to detect, prevent and arrest cascading failures in coupled socio-technical networks; and (iv) Understanding the co-evolution between the networks and dynamics, and using this to refine their models, and the strategies to control them. The broader impacts of this work include bridging the gap between the social sciences and computer science in addressing fundamental questions in complex networks, a corresponding enhancement to course curricula, and the involvement of students at all levels.