Exploring Word-Adjacency Networks with Multifractal Time Series Analysis Techniques

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Argitaratua izan da:Entropy vol. 27, no. 4 (2025), p. 356
Egile nagusia: Dec Jakub
Beste egile batzuk: Dolina Michał, Drożdż Stanisław, Kluszczyński, Robert, Kwapień Jarosław, Stanisz Tomasz
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MDPI AG
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100 1 |a Dec Jakub  |u Faculty of Computer Science and Telecommunications, Cracow University of Technology, 31-155 Kraków, Poland 
245 1 |a Exploring Word-Adjacency Networks with Multifractal Time Series Analysis Techniques 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a A novel method of exploring linguistic networks is introduced by mapping word-adjacency networks to time series and applying multifractal analysis techniques. This approach captures the complex structural patterns of language by encoding network properties—such as clustering coefficients and node degrees—into temporal sequences. Using Alice’s Adventures in Wonderland by Lewis Carroll as a case study, both traditional word-adjacency networks and extended versions that incorporate punctuation are examined. The results indicate that the time series derived from clustering coefficients, when following the natural reading order, exhibits multifractal characteristics, revealing inherent complexity in textual organization. Statistical validation confirms that observed multifractal properties arise from genuine correlations rather than from spurious effects. Extending this analysis by taking into account punctuation equally with words, however, changes the nature of the global scaling to a more convolved form that is not describable by a uniform multifractal. An analogous analysis based on the node degrees does not show such rich behaviors, however. These findings reveal a new perspective for quantitative linguistics and network science, providing a deeper understanding of the interplay between text structure and complex systems. 
653 |a Linguistics 
653 |a Punctuation 
653 |a Fractal analysis 
653 |a Case studies 
653 |a Time 
653 |a Words (language) 
653 |a Clustering 
653 |a Complexity 
653 |a Complex systems 
653 |a Sequences 
653 |a Networks 
653 |a Time series 
653 |a Text structure 
653 |a Semantics 
653 |a Property 
653 |a Mapping 
653 |a Encoding 
700 1 |a Dolina Michał  |u Faculty of Computer Science and Telecommunications, Cracow University of Technology, 31-155 Kraków, Poland 
700 1 |a Drożdż Stanisław  |u Faculty of Computer Science and Telecommunications, Cracow University of Technology, 31-155 Kraków, Poland 
700 1 |a Kluszczyński, Robert  |u Complex Systems Theory Department, Institute of Nuclear Physics, Polish Academy of Sciences, 31-342 Kraków, Poland 
700 1 |a Kwapień Jarosław  |u Complex Systems Theory Department, Institute of Nuclear Physics, Polish Academy of Sciences, 31-342 Kraków, Poland 
700 1 |a Stanisz Tomasz  |u Complex Systems Theory Department, Institute of Nuclear Physics, Polish Academy of Sciences, 31-342 Kraków, Poland 
773 0 |t Entropy  |g vol. 27, no. 4 (2025), p. 356 
786 0 |d ProQuest  |t Engineering Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3194594479/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text + Graphics  |u https://www.proquest.com/docview/3194594479/fulltextwithgraphics/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3194594479/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch