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Simulation Models for Diffusion over Multirelational Dynamic Networks

多关系动态网络上的扩散仿真模型

基本信息

批准号：
8239493
负责人：
James Moody
金额：
$ 23.06万
依托单位：
DUKE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-04-01 至 2014-03-31
项目状态：
已结题

项目摘要

DESCRIPTION (provided by applicant): Diffusion is a primary way in which social networks affect health, both directly, as when sexually transmitted diseases are passed between partners, and indirectly, as when norms about health relevant behavior travel through a social network. While crucial, with the exception of a few well specified and comparatively simple cases, the complexity of most network diffusion problems make analytic models cumbersome or intractable. As such, social simulations become an effective tool for understanding how network features affect population health, but we lack a generalized simulation framework, making it difficult to compare work across investigative teams. Thus, the primary aim of this project is to build a flexible network diffusion simulation system that accurately portrays dynamic, multi-relational social networks. The project makes use of newly- developed multi-slice network structures as a flexible tool for extending networks from static single-relation graphs to complex, evolving systems composed of multiple relations that can easily accommodate complex transmission rules. The fundamental insight of this proposal is twofold. Theoretically, it rests on the notion that complexity emerges naturally from the connections among simpler sub-systems. Methodologically, we operationalize linking of simpler sub-systems to a complex whole by using multi-slice network models. Thus, we first identify a generalized diffusion framework resting on differences in network structure along three dimensions and differences in dyadic transmission processes, also varying along three dimensions. Combined, these 6 complexity dimensions allow us to specify a network diffusion model that ranges from extremely simple (certain spread of a fixed pathogen over a static network) to complex (negotiated ideational diffusion across multiple evolving networks). The resulting simulation system will give health researchers across multiple domains the ability to model underlying network diffusion processes and answer clear questions about how features of the network structure affect health and health disparities. PUBLIC HEALTH RELEVANCE: At both the individual and population levels, health is affected by networks through a process of physical (as with infection spread) or social (as with peer influence) diffusion. Since analytic models for the vast majority of complex network diffusion situations are lacking, this project develops a generalized network simulation framework for health-relevant diffusion that can accommodate a wide variety of relevant situations. The result of this project is increased capacity to model the links between network structure, individual behavior, and the health status of individuals and communities.

描述（由申请人提供）：传播是社交网络影响健康的主要方式，既包括直接影响，如性传播疾病在伴侣之间传播，也包括间接影响，如健康相关行为规范通过社交网络传播。虽然至关重要，但除了少数指定和相对简单的情况外，大多数网络扩散问题的复杂性使分析模型变得繁琐或棘手。因此，社会模拟成为了解网络特征如何影响人口健康的有效工具，但我们缺乏一个通用的模拟框架，因此很难比较调查团队的工作。因此，本项目的主要目的是建立一个灵活的网络扩散模拟系统，准确地描绘动态的，多关系的社交网络。该项目利用新开发的多切片网络结构作为一种灵活的工具，将网络从静态的单一关系图扩展到由多种关系组成的复杂的、不断发展的系统，这些关系可以轻松地适应复杂的传输规则。这一建议的基本见解是双重的。从理论上讲，它依赖于这样一种概念，即复杂性自然地产生于较简单的子系统之间的联系。在方法上，我们操作简单的子系统连接到一个复杂的整体，通过使用多切片网络模型。因此，我们首先确定了一个广义的扩散框架上的差异网络结构沿着三个维度和差异的二元传输过程，也变化沿着三个维度。结合起来，这6个复杂性维度使我们能够指定一个网络扩散模型，范围从非常简单（固定病原体在静态网络上的某种传播）到复杂（在多个不断发展的网络中协商概念扩散）。由此产生的模拟系统将使跨多个领域的健康研究人员能够对底层网络扩散过程进行建模，并回答有关网络结构特征如何影响健康和健康差异的明确问题。公共卫生相关性：在个人和人口两个层面，网络通过物理（如感染传播）或社会（如同伴影响）扩散过程影响健康。由于分析模型的绝大多数复杂的网络扩散的情况是缺乏的，这个项目开发了一个通用的网络模拟框架，健康相关的扩散，可以适应各种各样的相关情况。该项目的结果是提高了对网络结构、个人行为以及个人和社区的健康状况之间的联系进行建模的能力。