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Investigating Centrality Measures in Social Networks with Community Structure

机译:侦查社区结构中社会网络中的中心措施

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Centrality measures are crucial in quantifying the influence of the members of a social network. Although there has been a great deal of work dealing with this issue, the vast majority of classical centrality measures are agnostic of the community structure characterizing many social networks. Recent works have developed community-aware centrality measures that exploit features of the community structure information encountered in most real-world complex networks. In this paper, we investigate the interactions between 5 popular classical centrality measures and 5 community-aware centrality measures using 8 real-world online networks. Correlation as well as similarity measures between both types of centrality measures are computed. Results show that community-aware centrality measures can be divided into two groups. The first group, which includes Bridging centrality, Community Hub-Bridge, and Participation Coefficient, provides distinctive node information as compared to classical centrality. This behavior is consistent across the networks. The second group which includes Community-based Mediator and Number of Neighboring Communities is characterized by more mixed results that vary across networks.
机译:中心措施对于量化社交网络成员的影响至关重要。虽然有大量的工作处理这个问题,但绝大多数古典中心措施是社区结构的不可知论,表征了许多社交网络。最近的作品已经开发了社区意识到的集中度措施,利用大多数现实世界复杂网络遇到的社区结构信息的特征。在本文中,我们研究了使用8个现实世界在线网络的5个受欢迎的古典中心措施和5个社区感知中心措施之间的相互作用。计算相关性以及两种类型的中心度措施之间的相似性测量。结果表明,社区意识的中心措施可分为两组。包括桥接中心,社区中心 - 桥梁和参与系数的第一组提供了与古典中心相比的独特节点信息。此行为在网络上是一致的。包括基于社区的调解员和邻近社区数量的第二组特征在于各种不同的混合结果。

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