Co-occurrence network of reuters news

被引:17
作者
Oezguer, Arzucan [1 ]
Cetin, Burak [2 ]
Bingol, Haluk [2 ]
机构
[1] Univ Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA
[2] Bogazici Univ, Dept Comp Engn, Complex Syst Res Lab, Istanbul, Turkey
来源
INTERNATIONAL JOURNAL OF MODERN PHYSICS C | 2008年 / 19卷 / 05期
关键词
social networks; importance of people; ranking; Wikipedia;
D O I
10.1142/S0129183108012431
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
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 and 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
引用
收藏
页码:689 / 702
页数:14
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