Rank Dynamics of Word Usage at Multiple Scales

Frontiers in Physics

Flores, Jorge¹  Morales, José²  Pineda, Carlos⁵  Gershenson, Carlos⁷  iguez, Gerardo⁷  A.⁷  Sá⁷  nchez, Sergio⁸  Iñ⁹  Colman, Ewan^1,10  nchez-Puig, Fernanda^1,10  Cocho, Germinal^1,10 

[1] Centro de Ciencias de la Complejidad, Universidad Nacional AutóFacultad de Ciencias, Universidad Nacional AutóFaculty of Physics, University of Vienna, Austria;Instituto de FíInstituto de Investigaciones en MatemáNext Games, Finland;noma de Mésica, Universidad Nacional Autóticas Aplicadas y en Sistemas, Universidad Nacional Autóxico, Mexico

关键词: culturomics;    N-grams;    language evolution;    rank diversity;    Complexity;   

DOI  :  10.3389/fphy.2018.00045

学科分类：物理（综合）

来源: Frontiers

【 摘 要 】

The recent dramatic increase in online data availability has allowed researchers to explore human culture with unprecedented detail, such as the growth and diversification of language. In particular, it provides statistical tools to explore whether word use is similar across languages, and if so, whether these generic features appear at different scales of language structure. Here we use the Google Books $N$-grams dataset to analyze the temporal evolution of word usage in several languages. We apply measures proposed recently to study rank dynamics, such as the diversity of $N$-grams in a given rank, the probability that an $N$-gram changes rank between successive time intervals, the rank entropy, and the rank complexity. Using different methods, results show that there are generic properties for different languages at different scales, such as a core of words necessary to minimally understand a language. We also propose a null model to explore the relevance of linguistic structure across multiple scales, concluding that $N$-gram statistics cannot be reduced to word statistics. We expect our results to be useful in improving text prediction algorithms, as well as in shedding light on the large-scale features of language use, beyond linguistic and cultural differences across human populations.

【 授权许可】

CC BY