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）：扩散是社交网络直接影响健康的主要方式，就像在伴侣之间和间接传播性传播疾病时一样，就像有关健康相关行为的规范通过社交网络传播时。虽然至关重要，但除了一些明确且相对简单的情况外，大多数网络扩散问题的复杂性使分析模型变得麻烦或棘手。因此，社交模拟成为了解网络特征如何影响人群健康的有效工具，但是我们缺乏广义的模拟框架，因此很难比较整个调查团队的工作。因此，该项目的主要目的是建立一个灵活的网络扩散模拟系统，该系统准确地描绘了动态的，多关系的社交网络。该项目利用新开发的多层网络结构作为一种灵活的工具，可将网络从静态单相关图扩展到复杂的，不断发展的系统，该系统由多个关系组成，可以轻松适应复杂的传输规则。该提议的基本见解是双重的。从理论上讲，它基于这样一种观念，即复杂性自然而然地来自简单的子系统之间的联系。从方法上讲，我们通过使用多板块网络模型将更简单的子系统链接到复杂整体。因此，我们首先确定沿着三个维度的网络结构差异以及二元传输过程的差异，沿三个维度也有所不同。结合在一起，这6个复杂性维度使我们能够指定一个网络扩散模型，该模型从极其简单（固定病原体在静态网络上的某些传播）到复杂（协商在多个不断发展的网络中的构思扩散）。由此产生的仿真系统将使跨多个领域的健康研究人员能够建模潜在的网络扩散过程，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：在个人和人口水平上，健康都通过身体（与感染传播一样）或社会（与同伴影响力的）扩散的过程受到网络的影响。由于缺乏绝大多数复杂网络扩散情况的分析模型，因此该项目为与健康相关的扩散开发了一个广义的网络模拟框架，可以适应各种相关情况。该项目的结果是增加了建模网络结构，个人行为与个人和社区健康状况之间的联系的能力。