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Exploring Word-Adjacency Networks with Multifractal Time Series Analysis Techniques.

Jakub Dec1, Michał Dolina1, Stanisław Drożdż1,2

  • 1Faculty of Computer Science and Telecommunications, Cracow University of Technology, 31-155 Kraków, Poland.

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Summary
This summary is machine-generated.

This study introduces a new method to analyze language structure using network mapping and multifractal analysis. The research reveals complex textual organization in literature, offering new insights for linguistics and network science.

Keywords:
clustring coefficientcomplex networksmultiscale correlationsquantitative linguisticstime seriesvertex observables

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Area of Science:

  • Quantitative Linguistics
  • Network Science
  • Complex Systems Analysis

Background:

  • Traditional linguistic analysis often overlooks the intricate structural patterns within texts.
  • Understanding the complex organization of language is crucial for advancements in computational linguistics and network theory.

Purpose of the Study:

  • To introduce a novel method for exploring linguistic networks by mapping word-adjacency networks to time series.
  • To apply multifractal analysis techniques to uncover complex structural patterns in textual data.
  • To investigate the impact of punctuation on linguistic network analysis.

Main Methods:

  • Mapping word-adjacency networks to time series data.
  • Applying multifractal analysis to temporal sequences derived from network properties (clustering coefficients, node degrees).
  • Case study using Lewis Carroll's "Alice's Adventures in Wonderland" with and without punctuation.

Main Results:

  • Time series derived from clustering coefficients exhibit multifractal characteristics, indicating inherent textual complexity.
  • Statistical validation confirmed the multifractal properties are genuine, not spurious.
  • Incorporating punctuation altered the scaling to a non-uniform multifractal form; node degree analysis showed less complexity.

Conclusions:

  • The proposed method offers a new perspective for quantitative linguistics and network science.
  • Multifractal analysis of linguistic networks reveals deep insights into text structure.
  • The study highlights the significant, yet complex, role of punctuation in textual organization.