Investigating Similarity of Nodes' Attributes in Topological Based Communities.

Rajesh Sharma, D. Montesi
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引用次数: 6

Abstract

One of the important problems in the domain of network science is the community detection. In the past, various topological based community detection algorithms have been proposed. Recently, researchers have taken into account at- tributes of the nodes while proposing community detection algorithms. In this work, we investigate if the nodes in a community, identified through topology based algorithms al- so exhibit attribute similarity. Using four different kinds of similarity metrics, we analyse the attribute similarity of the nodes within the communities derived using five different types of topological based community detection algorithms. Based on our analysis of three real social network datasets, we found on an average of 50% attribute similarity among the nodes in the communities.
基于拓扑的社区中节点属性相似性的研究。
社区检测是网络科学领域的一个重要问题。在过去,已经提出了各种基于拓扑的社区检测算法。近年来,研究人员在提出社区检测算法时考虑了节点的属性。在这项工作中,我们研究了通过基于拓扑的算法识别的社区中的节点是否表现出属性相似性。使用四种不同的相似度度量,分析了五种不同类型的基于拓扑的社区检测算法派生的社区内节点的属性相似度。基于我们对三个真实社交网络数据集的分析,我们发现社区节点之间的属性相似性平均为50%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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