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Publikācija: Co-occurrence of the Benford-like and Zipf Laws Arising from the Texts Representing Human and Artificial Languages

Publication Type Publication (reviewed) in journals with editorial board published in Latvia or abroad, including institutional juornals
Funding for basic activity Other research projects
Defending: ,
Publication language English (en)
Title in original language Co-occurrence of the Benford-like and Zipf Laws Arising from the Texts Representing Human and Artificial Languages
Field of research 2. Engineering and technology
Sub-field of research 2.2 Electrical engineering, Electronic engineering, Information and communication engineering
Authors Evgeny Shulzinger
Irina Legchenkova
Edward Bormashenko
Keywords human language ; artificial language; Zipf’s law; Benford’s law; qualitative linguistics
Abstract We demonstrate that large texts, representing human (English, Russian, Ukrainian) and artificial (C++, Java) languages, display quantitative patterns characterized by the Benford - like and Zipf laws. The frequency of a word following the Zipf law is inversely proportional to its rank, whereas the total numbers of a certain word appearing in the text generate the uneven Benford - like distribution of leading numbers. Excluding the most popular words essentially improves the correlation of actual textual data with the Zipfian distribution, whereas the Benford distribution of leading numbers (arising from the overall amount of a certain word) is insensitive to the same elimination procedure. The calculated values of the moduli of slopes of double logarithmical plots for artificial languages (C++, Java) are markedly larger than those for human ones.
Hyperlink: https://arxiv.org/abs/1803.03667 
Reference Shulzinger, E., Legchenkova, I., Bormashenko, E. Co-occurrence of the Benford-like and Zipf Laws Arising from the Texts Representing Human and Artificial Languages. arXiv, 2018, 1803.03667, pp.1-1. ISSN 2331-8422.
ID 28584