Japanese Kanji characters are small-world connected through shared components

We investigate the connectivity within different incre- mental sets of Japanese Kanji characters. Individual characters constitute the vertices in the network, components shared between them provide their edges. We find the resulting networks to have a high clustering coefficient and a low average path length, characterizing them as small worlds. We examine the statistical significance of these findings and the role of the degree distributions. We review the evidence that the small-world topologies of these networks are due to the successive elimination of components in the writing system and discuss the implications of the results for language evolution.

[1]  Agata Fronczak,et al.  Average path length in random networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.

[2]  Shuigeng Zhou,et al.  An empirical study of Chinese language networks , 2008 .

[3]  Ken Yamamoto,et al.  Network of two-Chinese-character compound words in Japanese language , 2009, ArXiv.

[4]  Tadao Miyamoto,et al.  The Evolution of Writing Systems: Against the Gelbian Hypothesis , 2003, JSAI Workshops.

[5]  Ricard V. Solé,et al.  Least effort and the origins of scaling in human language , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[6]  Olaf Sporns,et al.  The small world of the cerebral cortex , 2007, Neuroinformatics.

[7]  George Kingsley Zipf,et al.  Human behavior and the principle of least effort , 1949 .

[8]  James W. Heisig.  A complete course on how not to forget the meaning and writing of Japanese characters , 1977 .

[9]  I. J. Gelb.  A study of writing : the foundations of grammatology , 1953 .

[10]  Duncan J. Watts,et al.  Collective dynamics of ‘small-world’ networks , 1998, Nature.

[11]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[12]  Cees van Leeuwen,et al.  Emergence of scale-free network with chaotic units , 2003 .

[13]  Ramon Ferrer i Cancho,et al.  The small world of human language , 2001, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[14]  Michael Breakspear,et al.  Fragmentation: loss of global coherence or breakdown of modularity in functional brain architecture? , 2011, Front. Syst. Neurosci..

[15]  Ramon Ferrer-i-Cancho,et al.  Optimization Models of Natural Communication , 2014, J. Quant. Linguistics.

[16]  William S. Yamamoto,et al.  AY's Neuroanatomy of C. elegans for Computation , 1992 .

[17]  Ken Yamamoto,et al.  Structure and modeling of the network of two-Chinese-character compound words in the Japanese language , 2014, ArXiv.

[18]  Yong Li,et al.  Structural organization and scale-free properties in Chinese Phrase Networks , 2005 .

[19]  Stanley Wasserman,et al.  Social Network Analysis: Methods and Applications , 1994, Structural analysis in the social sciences.

[20]  Olaf Sporns,et al.  Symbiotic relationship between brain structure and dynamics , 2009, BMC Neuroscience.

[21]  Sun Maosong.  Chinese Word Co-occurrence Network:Its Small World Effect and Scale-free Property , 2007 .

[22]  K. Sneppen,et al.  Specificity and Stability in Topology of Protein Networks , 2002, Science.

[23]  Pulin Gong,et al.  Evolution to a small-world network with chaotic units , 2004 .

[24]  Chi K. Tse,et al.  Structural Equivalence Between Co-occurrences of Characters and Words in the Chinese Language , 2008 .

[25]  M. Young,et al.  Computational analysis of functional connectivity between areas of primate cerebral cortex. , 2000, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[26]  Jianyu Li,et al.  Chinese character structure analysis based on complex networks , 2007 .

[27]  D. van den Berg,et al.  Adaptive rewiring in chaotic networks renders small-world connectivity with consistent clusters , 2004 .