Title of article
Power-law link strength distribution in paper cocitation networks
Author/Authors
Star X. Zhao1، نويسنده , , Fred Y. Ye2، نويسنده , , *، نويسنده ,
Issue Information
ماهنامه با شماره پیاپی سال 2013
Pages
10
From page
1480
To page
1489
Abstract
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.
Keywords
information flow , sociocultural aspects , international aspects , technology impact , Information policy
Journal title
Journal of the American Society for Information Science and Technology
Serial Year
2013
Journal title
Journal of the American Society for Information Science and Technology
Record number
994901
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