JSEA  Vol.1 No.1 , December 2008
Motif-based Classification in Journal Citation Networks
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.

Cite this paper
nullW. Wu, Y. Han and D. Li, "Motif-based Classification in Journal Citation Networks," Journal of Software Engineering and Applications, Vol. 1 No. 1, 2008, pp. 53-59. doi: 10.4236/jsea.2008.11008.
References
[1]   D. J. Watts and S. H. Strogatz, “Collective dynamics of ‘small-world’ networks,” Nature, 393(6684): pp. 440-442, 1998.

[2]   A. L. Barabasi and R. Albert, “Emergence of scaling in random networks,” Science, 286(5439): pp. 509-512, 1999.

[3]   R. Milo, S. Shen-Orr, et al., “Network motifs: Simple building blocks of complex networks,” Science, 298: pp. 824-827, 2002.

[4]   T. I. Lee, et al., “Transcriptional regulatory networks in Saccharomyces cerevisiae,” Science, 298: pp. 799-804, 2002.

[5]   D. T. Odom, et al., “Control of pancreas and liver gene expression by HNF transcription factors,” Science, 303: pp. 1378-1381, 2004.

[6]   N. Iranfar, D. Fuller, and W. F. Loomis, “Transcriptional regulation of post-aggregation genes in Dictyostelium by a feed-forward loop involving GBF and LagC,” Developmental Biology, 290: pp. 460-469, 2006.

[7]   R. Prill, P. Iglesias, and A. Levchenko, “Dynamic properties of network motifs contribute to biological network organization,” PLoS Biology, 3: pp. e343, 2005.

[8]   E. Ravasz, A. L. Somera, D. A. Mongru, et al., “Hierarchical organization of modularity in metabolic networks,” Science, 297: pp. 1551-1555, 2002.

[9]   R. Milo, S. Itzkovitz, N. Kashtan, et al., “Superfamilies of evolved and designed networks,” Science, 303: pp. 1538- 1542, 2004.

[10]   P. Zhou, L. Leydesdorff, and Y. S. Wu, “The visualization of Chinese Journal of Scientific and Technic in citation environment,” http://users.fmg.uva.nl/lleydesdorff/istic03/index.htm.

[11]   G. Kossinets and D. J. Watts, “Empirical analysis of an evolving social network,” Science, 331: pp. 88-90, 2006.

[12]   M. Girvan and M. E. J. Newman, “Community structure in social and biological networks,” Proceedings of the National Academy of Sciences, 99: pp. 7821-7826, 2002.

[13]   J. Tyler, D. Wilkison, B. Huberman, “Email as spectroscopy: Automated discovery of community structure within organizations,” International Conference on Communities and Technologies, pp. 81-96, 2003.

[14]   F. Radicchi, C. Castellano, F. Cecconi, V. Loreto, and D. Parisi, “Defining and identifying communities in networks,” Proceedings of the National Academy of Sciences, 101: pp. 2658-2663, 2004.

[15]   S. Fortunato, V. Latora, and M. Marchiori, “A method to find community structures based on information centrality,” Physical Review E, 70: 056104, 2004.

[16]   M. E. J. Newman, “Fast algorithm for detecting community structure in networks,” Physical Review E, 69: 066133, 2004.

[17]   G. Palla, I. Derényi, I. Farkas, and T. Vicsek, “Uncovering the overlapping community structure of complex networks in nature and society,” Nature, 435 (7043): pp. 814-818, 2005.

 
 
Top