title: A common construction pattern of English words and Chinese characters.
abstract: Rankings are ubiquitous around the world. Here I investigate spatial ranking patterns of English Words and Chinese Characters, and reveal a common construction pattern related to phase separation. In detail, I analyze a list of different words in the English language, and find that the frequency of the number of letters per word linearly or nonlinearly decays over its rank in the frequency table. I interpret the linearly decaying area as a linear phase that covers 96.4% words, which is in sharp contrast to a nonlinear phase (representing the nonlinearly decaying area) that covers the remaining 3.6% words. Amazingly, the phase separation phenomenon with the same two percentages of 96.4% and 3.6% holds also for the relation between strokes and characters in the Chinese language although English and Chinese are two distinctly different language systems. The common construction pattern originates from the log-normal distributions of frequencies of words or characters, which can be understood by the joint effect of both the Weber-Fechner law in psychophysics and the principle of maximum entropy in information theory.
authors.affiliation: Department of Physics and State Key Laboratory of Surface Physics, Fudan University, Shanghai, China.
authors.forename: Jiping
authors.initials: J
authors.lastname: Huang
mesh_terms: D016014:Linear Models; D008037:Linguistics; D017711:Nonlinear Dynamics; D010363:Pattern Recognition, Automated
references.citation: Phys Rev Lett. 2008 Nov 21;101(21):218701
references.pmid: 19113459
references.citation: Nature. 2007 Oct 11;449(7163):713-6
references.pmid: 17928859
references.citation: Proc Natl Acad Sci U S A. 2009 May 26;106(21):8423-8
references.pmid: 19435846
references.citation: J R Soc Interface. 2012 Dec 7;9(77):3323-8
references.pmid: 22832364
references.citation: PLoS One. 2012;7(7):e40393
references.pmid: 22815745
references.citation: PLoS One. 2013;8(3):e53227
references.pmid: 23516390
references.citation: Phys Rev E Stat Nonlin Soft Matter Phys. 2013 Jan;87(1):012809
references.pmid: 23410390
references.citation: Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Mar;83(3 Pt 2):036115
references.pmid: 21517566
references.citation: Sci Rep. 2013;3:1082
references.pmid: 23378896
references.citation: Phys Rev Lett. 1987 Jul 27;59(4):381-384
references.pmid: 10035754
references.citation: Phys Rev Lett. 2003 Feb 28;90(8):088102
references.pmid: 12633463
references.citation: Sci Rep. 2012;2:943
references.pmid: 23230508
references.citation: BMC Bioinformatics. 2012 Jun 07;13:127
references.pmid: 22676436
references.citation: Phys Rev E Stat Nonlin Soft Matter Phys. 2012 May;85(5 Pt 1):051309
references.pmid: 23004752
references.citation: Phys Rev Lett. 2012 Sep 21;109(12):128701
references.pmid: 23005999
references.citation: Phys Rev E Stat Nonlin Soft Matter Phys. 2010 Jul;82(1 Pt 1):011102
references.pmid: 20866560
references.citation: PLoS One. 2012;7(3):e33993
references.pmid: 22479497
references.citation: Nature. 2011 Jun 08;474(7350):164-5
references.pmid: 21654791
references.citation: Phys Rev Lett. 2009 Nov 20;103(21):218701
references.pmid: 20366071
references.citation: Proc Natl Acad Sci U S A. 2003 Feb 4;100(3):788-91
references.pmid: 12540826
references.citation: Proc Natl Acad Sci U S A. 2010 Oct 26;107(43):18325-30
references.pmid: 20937903
references.citation: Science. 2001 Sep 7;293(5536):1818-20
references.pmid: 11546870
references.citation: Phys Rev Lett. 1995 May 29;74(22):4559-4562
references.pmid: 10058537
references.citation: Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Aug;84(2 Pt 2):026117
references.pmid: 21929074