Cluster structures in topology of large-scale social networks revealed by traffic data
Cluster structures in topology of large-scale social networks revealed by traffic data
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DOI：
10.1109/glocom.2005.1577350
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发表时间：
2005
期刊：
影响因子：
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通讯作者：
Masaki Aida;K. Ishibashi;C. Takano;H. Miwa;Kaori Muranaka;A. Miura
中科院分区：
文献类型：
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作者：
Masaki Aida;K. Ishibashi;C. Takano;H. Miwa;Kaori Muranaka;A. Miura
最近发表了许多关于社交网络的研究。对拓扑结构的兴趣，如无标度特性，一直特别强烈。在本文中，我们专注于宏观流量数据的分析，在一个通信网络的手机用户作为一种方式，调查大规模的社交网络。移动电话用户对之间的信息交换行为反映在流量数据中，从而反映了社交网络的有趣特征。我们分析了客户数量和流量之间的关系，以期在庞大的潜在客户群中找到有关社交网络结构的线索。然后，我们展示了一些有趣的功能，我们的分析揭示：一个无标度拓扑的人际关系，他们的集群结构，和用户动态行为。此外，我们根据情况考虑交通量和客户数量之间的关系。
Many studies of social networks have recently been published. Interest in topological structures, such as scale-free characteristics, has been particularly strong. In this paper, we focus on the analysis of macro traffic data in a communications network of cellular phone users as a way of investigating large-scale social networks. Behaviors of information exchange between pairs of cellular phone users are reflected in traffic data, which thus reflects interesting features of social networks. We analyze the relationship between the number of customers and the volume of traffic with a view to finding clues about the structure of social networks among the very large set of potential customers. We then demonstrate some interesting features that our analysis reveals: a scale-free topology of human relations, their cluster structures, and behaviors of user-dynamics. In addition, we consider the relationship between traffic volume and the number of customers depending on the situation.