NeTS: Small: Collaborative Research: Multi-Resolution Analysis & Measurement of Large-scale, Dynamic Networked Systems with Applications to Online Social Networks

NeTS：小型：协作研究：多分辨率分析

• 批准号: 0917381
• 负责人: Reza Rejaie
• 金额: $ 35.5万
• 依托单位: University of Oregon Eugene
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-15 至 2014-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0917381&HistoricalAwards=false
• 关键词: NeTS; Small; Collaborative; Research; Multi

Many large-scale networked systems such as Online Social Networks (OSNs)are often represented as annotated graphs with various node or link attributes. Such a representation is usually derived from a snapshot that is obtained through measurements. These graph representations enable researchers to characterize the connectivity of these systems using graph analysis. However, captured snapshots of large networked systems are likely to be distorted. Furthermore, commonly-used graph analysis characterizes the connectivity of a graph in an indirect fashion and generally ignores graph dynamics.This multi-disciplinary research program designs, develops and rigorously evaluates theoretically grounded techniques to accurately measure and properly characterize the connectivity structure of large-scale and dynamic networked systems. More specifically, the project examines various graph sampling techniques for collecting representative samples from large and evolving graphs. It also investigates how multiscale analysis can be used as a powerful technique to characterize the key features of the connectivity structure of large dynamic networked systems at different scales in space and time. The developed techniques will be used to characterize fundamental properties of the friendship and various interaction connectivity structures in different OSNs.This project promises to identify the underlying technical and social factors that primarily drive the structural properties and dynamic nature of OSN-specific connectivity structures. It will produce new models for friendship and interactions in OSNs, a large archive of anonymized datasets and new tools for OSN measurement, simulation and analysis. The latter will be incorporated into newly-developed courses in Computer Science and Sociology, and will be freely distributed.

在线社交网络（OSN）等大规模网络系统通常表示为具有各种节点或链路属性的带注释的图。这种表示通常是从通过测量获得的快照中导出的。这些图形表示使研究人员能够使用图形分析来表征这些系统的连通性。然而，大型网络系统的捕获快照可能会失真。此外，常用的图分析以间接的方式表征图的连通性，通常忽略了图的动态性。这个多学科的研究计划设计，开发和严格评估理论基础技术，以准确测量和正确表征大规模和动态网络系统的连通性结构。更具体地说，该项目研究了各种图形采样技术，用于从大型和不断发展的图形中收集代表性样本。它还研究了如何多尺度分析可以被用来作为一个强大的技术来表征在不同尺度的空间和时间的大型动态网络系统的连接结构的关键特征。所开发的技术将用于表征友谊的基本属性和不同的OSNs中的各种交互连接结构。该项目有望确定主要驱动OSN特定连接结构的结构属性和动态性质的潜在技术和社会因素。它将为OSN中的友谊和交互产生新的模型，一个大型的匿名数据集档案和OSN测量，模拟和分析的新工具。后者将被纳入新开发的计算机科学和社会学课程，并将免费分发。