Power-law link strength distribution in paper cocitation networks

被引:17
作者
Zhao, Star X. [1 ]
Ye, Fred Y. [2 ]
机构
[1] Zhejiang Univ, Dept Informat Resource Management, Hangzhou 310027, Peoples R China
[2] Nanjing Univ, Sch Informat Management, Nanjing 210093, Jiangsu, Peoples R China
来源
JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY | 2013年 / 64卷 / 07期
基金
中国国家自然科学基金;
关键词
information flow; international aspects; sociocultural aspects; information policy; technology impact; INFORMATION-SCIENCE; CITATION NETWORK; KNOWLEDGE; RELEVANCE; PAGERANK; MAPS;
D O I
10.1002/asi.22846
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A network is constructed by nodes and links, thus the node degree and the link strength appear as underlying quantities in network analysis. While the power-law distribution of node degrees is verified as a basic feature of numerous real networks, we investigate whether the link strengths follow the power-law distribution in weighted networks. After testing 12 different paper cocitation networks with 2 methods, fitting in double-log scales and the Kolmogorov-Smirnov test (K-S test), we observe that, in most cases, the link strengths also follow the approximate power-law distribution. The results suggest that the power-law type distribution could emerge not only in nodes and informational entities, but also in links and informational connections.
引用
收藏
页码:1480 / 1489
页数:10
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