Computational Study of Stylistics: Visualizing the Writing Style with Self-Organizing Maps

  • Antonio Neme
  • Sergio Hernández
  • Teresa Dey
  • Abril Muñoz
  • J. R. G. Pulido
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 198)


The style authors follow to express their ideas has been a subject of great debate. Several perspectives have been followed to try to analyze the style. In this contribution we present a computational methodology to study the writing style in a collection of hundreds of texts. For each text several attributes, which include different time series, are extracted and a battery of tools from the signal processing and the machine learning communities are applied to identify a set of features that may define a candidate style space. We applied self-organizing maps to visualize how several authors are distributed in the high-dimensional space associated to the style, and to visually prospect the similarities between styles from different authors.


computational stylistics authorship attribution visualization self-organizing maps mutual information 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Antonio Neme
    • 1
    • 2
  • Sergio Hernández
    • 3
  • Teresa Dey
    • 4
  • Abril Muñoz
    • 5
  • J. R. G. Pulido
    • 6
  1. 1.Complex Systems GroupUniversidad Autónoma de la Ciudad de MéxicoMéxicoD.F. México
  2. 2.Institute for Molecular MedicineHelsinkiFinland
  3. 3.Postgraduation Program in Complex SystemsUniversidad Autónoma de la Ciudad de MéxicoMéxicoMéxico
  4. 4.Faculty of Literary CreationUniversidad Autónoma de la Ciudad de MéxicoMéxicoMéxico
  5. 5.CINVESTAV IDSMexicoMéxico D.F.
  6. 6.Facultad de TelemáticaUniversidad de ColimaMéxicoMéxico

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