PROPERTIES OF AUTOSEMANTIC WORD NETWORKS IN UKRAINIAN TEXTS

Solomija Buk (), Yuri Krynytskyi () and Andrij Rovenchak
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Solomija Buk: Department for General Linguistics, Ivan Franko National University of Lviv, 1, Universytetska St., Lviv, Ukraine
Yuri Krynytskyi: Department for Theoretical Physics, Ivan Franko National University of Lviv, 12, Drahomanov St., Lviv, Ukraine
Andrij Rovenchak: Department for Theoretical Physics, Ivan Franko National University of Lviv, 12, Drahomanov St., Lviv, Ukraine

Advances in Complex Systems (ACS), 2019, vol. 22, issue 06, 1-22

Abstract: We present results of network analysis of Ukrainian texts. Autosemantic (meaningful) words are considered as network vertices connected with links when belonging to one sentence. Subnetworks corresponding to specific parts of speech (verbs, nouns, adjectives, etc.) are also built. The obtained networks are small-world and scale-free. To make comparisons, random texts with parameters corresponding to real texts are generated using several approaches. Various parameters of networks are calculated, including transitivity, betweenness, degree centralization, mean distance, network diameter, exponents of degree distribution, etc. Comparison of network parameters of real and generated texts shows that borders between them are quite fuzzy.

Keywords: Language networks; scale-free networks; random text generation (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:wsi:acsxxx:v:22:y:2019:i:06:n:s0219525919500164

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DOI: 10.1142/S0219525919500164

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