论文标题
盗贼游戏与复杂网络中其他中心度度量之间的相关性
Correlations among Game of Thieves and other centrality measures in complex networks
论文作者
论文摘要
社交网络分析（SNA）用于研究个人，群体或组织之间的资源交换。一组中心度指标描述了个体或连接在网络中的作用，这些集中度指标代表了SNA的最重要结果之一。程度，亲密度，中间和聚类系数是最常用的中心度度量。但是，它们的计算成本严重阻碍了它们的使用。这个问题可以通过一种称为盗贼游戏（GOT）的算法来克服。多亏了这种新算法，我们可以计算网络中所有元素的重要性（即顶点和边缘），与顶点总数相比。该计算不是在二次时间内完成的，就像我们使用经典方法时，而是在Polyrogarithmic的时间中进行的。从此开始，我们介绍了GOT和最广泛使用的中心度度量之间存在的相关性。从我们的实验中出现了存在很强的相关性，这使得成为大规模复杂网络的中心度度量的资格。
Social Network Analysis (SNA) is used to study the exchange of resources among individuals, groups, or organizations. The role of individuals or connections in a network is described by a set of centrality metrics which represent one of the most important results of SNA. Degree, closeness, betweenness and clustering coefficient are the most used centrality measures. Their use is, however, severely hampered by their computation cost. This issue can be overcome by an algorithm called Game of Thieves (GoT). Thanks to this new algorithm, we can compute the importance of all elements in a network (i.e. vertices and edges), compared to the total number of vertices. This calculation is done not in a quadratic time, as when we use the classical methods, but in polylogarithmic time. Starting from this we present our results on the correlation existing between GoT and the most widely used centrality measures. From our experiments emerge that a strong correlation exists, which makes GoT eligible as a centrality measure for large scale complex networks.
