路透社新闻同现网
Co-occurrence Network of Reuters News
摘要：
网络描述了各种复杂的自然系统，包括社会系统。我们调查的社会网络的共现路透社-21578语料库，其中包括新闻文章，出现在路透社新闻专线在1987年。人被表示为顶点，如果两个人在同一篇文章中同时出现，则他们是相连的。该网络具有幂律度分布的小世界特征。网络是不连通的，组分的粒度分布具有幂律特征。度缩减网络上的社区检测提供了有意义的社区。一个只包含强连接的边缩减网络具有星型拓扑。调查人员的“重要性”。网络是1987年的情况。20年后，对人民的重要性可以做一个更好的判断。许多排名算法，包括Citation count，PageRank，用于为顶点分配排名。算法给出的排名与维基百科中一个人的表现进行比较。我们发现了中等水平的斯皮尔曼等级相关性。一个值得注意的发现是，PageRank始终比其他算法表现得更差。我们进一步分析并找出原因。
英文摘要：
Networks describe various complex natural systems including social systems. We investigate the social network of co-occurrence in Reuters-21578 corpus, which consists of news articles that appeared in the Reuters newswire in 1987. People are represented as vertices and two persons are connected if they co-occur in the same article. The network has small-world features with power-law degree distribution. The network is disconnected and the component size distribution has power law characteristics. Community detection on a degree-reduced network provides meaningful communities. An edge-reduced network, which contains only the strong ties has a star topology. "Importance" of persons are investigated. The network is the situation in 1987. After 20 years, a better judgment on the importance of the people can be done. A number of ranking algorithms, including Citation count, PageRank, are used to assign ranks to vertices. The ranks given by the algorithms are compared against how well a person is represented in Wikipedia. We find up to medium level Spearman's rank correlations. A noteworthy finding is that PageRank consistently performed worse than the other algorithms. We analyze this further and find reasons.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
