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首页> 外文期刊>International Journal of Modern Physics, C. Physics and Computers >Limitation of degree information for analyzing the interaction evolution in online social networks
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Limitation of degree information for analyzing the interaction evolution in online social networks

机译:在线社交网络中互动发展分析的程度信息的局限性

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摘要

Previously many studies on online social networks simply analyze the static topology in which the friend relationship once established, then the links and nodes will not disappear, but this kind of static topology may not accurately reflect temporal interactions on online social services. In this study, we define four types of users and interactions in the interaction (dynamic) network. We found that active, disappeared, new and super nodes (users) have obviously different strength distribution properties and this result also can be revealed by the degree characteristics of the unweighted interaction and friendship (static) networks. However, the active, disappeared, new and super links (interactions) only can be reflected by the strength distribution in the weighted interaction network. This result indicates the limitation of the static topology data on analyzing social network evolutions. In addition, our study uncovers the approximately stable statistics for the dynamic social network in which there are a large variation for users and interaction intensity. Our findings not only verify the correctness of our definitions, but also helped to study the customer churn and evaluate the commercial value of valuable customers in online social networks.
机译:以前,许多关于在线社交网络的研究只是简单地分析了一旦建立了朋友关系的静态拓扑,那么链接和节点就不会消失,但是这种静态拓扑可能无法准确反映在线社交服务上的时间交互。在这项研究中,我们在交互(动态)网络中定义了四种类型的用户和交互。我们发现活动节点,消失节点,新节点和超级节点(用户)具有明显不同的强度分布属性,并且该结果也可以通过未加权的交互和友谊(静态)网络的程度特征来揭示。但是,活动的,消失的,新的和超级的链接(交互)只能通过加权交互网络中的强度分布来反映。该结果表明静态拓扑数据在分析社交网络演变方面的局限性。此外,我们的研究还发现了动态社交网络的近似稳定统计数据,其中用户和交互强度存在较大差异。我们的发现不仅验证了我们定义的正确性,而且还有助于研究客户流失并评估在线社交网络中有价值客户的商业价值。

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