利用网络科学识别社会网络中的中心性测度

Amit Kumar Yadav, R. Johari, Raman Dahiya
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引用次数: 3

摘要

世界有许多复杂的系统,每个系统都由各种较小的组件组成。网络科学已被用于研究复杂系统,如具有众多神经元的大脑、互联网、商业连接等领域。本文主要研究网络科学、社会网络分析和识别中心性测度。在进一步的过程中,应用R代码找到样本网络的中心性度量,并使用网络科学,纽曼-格文算法对从USDS (USICT学生数据集)收集的真实数据集进行社区检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification of Centrality Measures in Social Network using Network Science
World have many complex systems and each of them composed of various smaller components. Network science has been used to study the complex system like Brain with numerous neurons, Internet, Business Connection and within other domains. This paper focused on study about Network Science, Social Network Analysis and identifying centrality measures using literature survey. In further process R code had applied to find Centrality measures of sample network and Community detection is done on real dataset gathered from USDS (USICT Student Dataset) using Network Science, Newman-Girvan Algorithm.
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