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: 1010921
• 负责人: Jurij Leskovec
• 金额: $ 50.35万
• 依托单位: Stanford University
• 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=1010921&HistoricalAwards=false
• 关键词: 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。