NetSE: Large: Collaborative Research: Contagion in Large Socio-Communication Networks

NetSE：大型：协作研究：大型社会通信网络中的传染

• 批准号: 1010789
• 负责人: Aravind Srinivasan
• 金额: $ 47.5万
• 依托单位: University of Maryland, College Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-15 至 2016-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1010789&HistoricalAwards=false
• 关键词: NetSE; Large; Collaborative; Research; Contagion; NetSE; Large; Collaborative; Research; Contagion

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.

简单的传染过程是复杂网络上各种现象的基础，例如社交接触网络上的疾病传播以及通信网络中的信息；了解他们的动态和开发控制机制是许多应用程序中的关键问题。该建议的目标是：（i）开发使用部分和嘈杂数据构建合成关系网络的方法； （ii）了解这些网络和传染过程的结构，以及对传播动态产生影响的尤其重要的网络属性和典型模式； （iii）开发技术来控制传染过程的传播，并在耦合的社会技术网络中检测，预防和阻止级联失败； （iv）了解网络与动态之间的共同发展，并使用它来完善其模型，以及控制它们的策略。