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
Link To Document :
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