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Multilayer network of language: A unified framework for structural analysis of linguistic subsystems

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  • Martinčić-Ipšić, Sanda
  • Margan, Domagoj
  • Meštrović, Ana

Abstract

Recently, the focus of complex networks’ research has shifted from the analysis of isolated properties of a system toward a more realistic modeling of multiple phenomena — multilayer networks. Motivated by the prosperity of multilayer approach in social, transport or trade systems, we introduce the multilayer networks for language. The multilayer network of language is a unified framework for modeling linguistic subsystems and their structural properties enabling the exploration of their mutual interactions. Various aspects of natural language systems can be represented as complex networks, whose vertices depict linguistic units, while links model their relations. The multilayer network of language is defined by three aspects: the network construction principle, the linguistic subsystem and the language of interest. More precisely, we construct a word-level (syntax and co-occurrence) and a subword-level (syllables and graphemes) network layers, from four variations of original text (in the modeled language). The analysis and comparison of layers at the word and subword-levels are employed in order to determine the mechanism of the structural influences between linguistic units and subsystems. The obtained results suggest that there are substantial differences between the networks’ structures of different language subsystems, which are hidden during the exploration of an isolated layer. The word-level layers share structural properties regardless of the language (e.g. Croatian or English), while the syllabic subword-level expresses more language dependent structural properties. The preserved weighted overlap quantifies the similarity of word-level layers in weighted and directed networks. Moreover, the analysis of motifs reveals a close topological structure of the syntactic and syllabic layers for both languages. The findings corroborate that the multilayer network framework is a powerful, consistent and systematic approach to model several linguistic subsystems simultaneously and hence to provide a more unified view on language.

Suggested Citation

  • Martinčić-Ipšić, Sanda & Margan, Domagoj & Meštrović, Ana, 2016. "Multilayer network of language: A unified framework for structural analysis of linguistic subsystems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 117-128.
    • Handle: RePEc:eee:phsmap:v:457:y:2016:i:c:p:117-128
    DOI: 10.1016/j.physa.2016.03.082
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    References listed on IDEAS

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    1. Matteo Barigozzi & Giorgio Fagiolo & Diego Garlaschelli, 2009. "Multinetwork of international trade: A commodity-specific analysis," Papers 0908.1879, arXiv.org, revised Jun 2010.
    2. Amancio, Diego R. & Nunes, Maria G.V. & Oliveira, Osvaldo N. & Costa, Luciano da F., 2012. "Extractive summarization using complex networks and syntactic dependency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1855-1864.
    3. Medeiros Soares, M. & Corso, G. & Lucena, L.S., 2005. "The network of syllables in Portuguese," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(2), pages 678-684.
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    Cited by:

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    3. Solomija Buk & Yuri Krynytskyi & Andrij Rovenchak, 2019. "Properties Of Autosemantic Word Networks In Ukrainian Texts," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 22(06), pages 1-22, December.
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    5. Sanda Martinčić-Ipšić & Edvin Močibob & Matjaž Perc, 2017. "Link prediction on Twitter," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-21, July.
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    7. Criado-Alonso, Ángeles & Battaner-Moro, Elena & Aleja, David & Romance, Miguel & Criado, Regino, 2021. "Enriched line graph: A new structure for searching language collocations," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    8. Woon Peng Goh & Kang-Kwong Luke & Siew Ann Cheong, 2018. "Functional shortcuts in language co-occurrence networks," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-18, September.

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