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 |
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MDPI AG
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| Sarrera elektronikoa: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 045 | 2 | |b d20250101 |b d20251231 | |
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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 |