全球智库信息集成服务系统(G2TT): Understanding Zipf's law of word frequencies through sample-space collapse in sentence formation.

G2TT

来源类型	Article
规范类型	其他
DOI	10.1098/rsif.2015.0330
	Understanding Zipf's law of word frequencies through sample-space collapse in sentence formation.
	Thurner S; Hanel R; Liu B; Corominas-Murtra B
发表日期	2015
出处	Interface 12 (108): 0330
出版年	2015
语种	英语
摘要	The formation of sentences is a highly structured and history-dependent process. The probability of using a specific word in a sentence strongly depends on the 'history' of word usage earlier in that sentence. We study a simple history-dependent model of text generation assuming that the sample-space of word usage reduces a long sentence formation, on average. We first show that the model explains the approximate Zipf law found in word frequencies as a direct consequence of sample-space reduction. We then empirically quantify the amount of sample-space reduction in the sentences of 10 famous English books, by analysis of corresponding word-transition tables that capture which words can follow any given word in a text. We find a highly nested structure in these transition tables and show that this 'nestedness' is tightly related to the power law exponents of the observed word frequency distributions. With the proposed model, it is possible to understand that the nestedness of a text can be the origin of the actual scaling exponent and that deviations from the exact Zipf law can be understood by variations of the degree of nestedness on a book-by-book basis. On a theoretical level, we are able to show that in the case of weak nesting, Zip's law breaks down in a fast transition. Unlike previous attempts to understand Zipf's law in language the sample-space reducing model is not based on assumptions of multiplicative, preferential or self-organized critical mechanisms behind language formation, but simply uses the empirically quantifiable parameter 'nestedness' to understand the statstics of word frequencies.
主题	Advanced Systems Analysis (ASA)
关键词	language formation random walks on networks scaling in stochastic processes word-transition networs
URL	http://pure.iiasa.ac.at/id/eprint/11401/
来源智库	International Institute for Applied Systems Analysis (Austria)
引用统计
资源类型	智库出版物
条目标识符	http://119.78.100.153/handle/2XGU8XDN/130330
推荐引用方式 GB/T 7714	Thurner S,Hanel R,Liu B,et al. Understanding Zipf's law of word frequencies through sample-space collapse in sentence formation.. 2015.