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首页> 外文期刊>International Journal of Information Technology and Computer Science >A New Centrality Measure for Tracking Online Community in Social Network
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A New Centrality Measure for Tracking Online Community in Social Network

机译:社交网络中在线社区追踪的新中心度度量

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摘要

This paper presents a centrality measurement and analysis of the social networks for tracking online community. The tracking of single community in social networks is commonly done using some of the centrality measures employed in social network community tracking. The ability that centrality measures have to determine the relative position of a node within a network has been used in previous research work to track communities in social networks using betweenness, closeness and degree centrality measures. It introduces a new metric K-path centrality, and a randomized algorithm for estimating it, and shows empirically that nodes with high K-path centrality have high node betweenness centrality.
机译:本文提出了用于跟踪在线社区的社交网络的集中度测量和分析。社交网络中单个社区的跟踪通常使用社交网络社区跟踪中使用的一些集中性度量来完成。先前的研究工作已经使用集中度度量来确定网络内节点的相对位置的能力,以使用中间性,亲密性和程度集中度度量来跟踪社交网络中的社区。它介绍了一种新的度量K路径中心度,以及用于估计它的随机算法,并从经验上表明,具有K路径中心度高的节点具有较高的节点间中心度。

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