论文标题
调查具有社区结构的社交网络中的中心措施
Investigating Centrality Measures in Social Networks with Community Structure
论文作者
论文摘要
中心措施对于量化社交网络成员的影响至关重要。尽管解决了这一问题的工作很多，但绝大多数的古典中心度措施对许多社交网络表征的社区结构不可知。最近的工作开发了社区意识的中心度度量，这些措施利用了大多数现实世界中复杂网络中遇到的社区结构信息的特征。在本文中，我们研究了使用8种实际的在线网络进行5种流行的古典中心度度量与5种社区意识的中心度度量之间的相互作用。计算两种类型的中心度度量之间的相关性以及相似性度量。结果表明，社区意识的中心度度量可以分为两组。与经典的中心性相比，第一组包括桥接中心，社区枢纽和参与系数，提供了独特的节点信息。这种行为在整个网络之间是一致的。包括基于社区的调解人和邻近社区数量的第二组的特征是各个网络各不相同的结果。
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 type 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.
