Abstract
Journals and their citation relations are abstracted into journal citation networks, basing on CSTPC journal database from year 2003 to 2006. The network shows some typical characteristics from complex networks. This paper presents the idea of using motifs, subgraphs with higher occurrence in real network than in random ones, to discover two different citation patterns in journal communities. And a further investigation is addressed on both motif granularity and node centrality to figure out some reasons on the differences between two kinds of communities in journal citation network.
Highlights
As an effective method, complex networks have been widely used to describe many complicated real world systems
Recent researches indicate that network motifs, interconnected patterns occurring in numbers that are significantly higher than those in identical randomized networks, may be the “simple building blocks” in complex networks [3]
Ron Milo proposed two concepts in 2002, which are shown below to find motifs in networks. They gave the concept of “superfamilies” in 2004 and the significance profile (SP) method to compare the local structure between different kinds of complex networks [9]
Summary
Complex networks have been widely used to describe many complicated real world systems. The same motifs, defined as feed-forward loops, have been found in organisms from bacteria and yeast [4], to plants and animals [5,6] This kind of motifs plays an important role of persistence detectors, or pulse generator and response accelerators. Ron Milo proposed two concepts in 2002, which are shown below to find motifs in networks They gave the concept of “superfamilies” in 2004 and the significance profile (SP) method to compare the local structure between different kinds of complex networks [9]. P-Value means the probability of network motifs appearing in a randomized network an equal or greater number of times than in the real network Milo and his fellows published the motif detection software, named MFinder in the homepage of Uri Alon lab.
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