Computational study of stylistics: Visualizing the writing style with self-organizing maps


Por: Neme A., Hernández S., Dey T., Muñoz A., Pulido J.R.G.

Publicada: 1 ene 2013
Resumen:
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. © 2013 Springer-Verlag.

Filiaciones:
Neme A.:
 Complex Systems Group, Universidad Autónoma de la Ciudad de México, San Lorenzo 290, México, D.F., Mexico

 Institute for Molecular Medicine, Helsinki, Finland

Hernández S.:
 Postgraduation Program in Complex Systems, Universidad Autónoma de la Ciudad de México, México, Mexico

Dey T.:
 Faculty of Literary Creation, Universidad Autónoma de la Ciudad de México, México, Mexico

Muñoz A.:
 CINVESTAV IDS, México D.F., Mexico

Pulido J.R.G.:
 Facultad de Telemática, Universidad de Colima, México, Mexico
ISSN: 21945357
Editorial
Springer Verlag, HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY, Alemania
Tipo de documento: Conference Paper
Volumen: 198 AISC Número:
Páginas: 265-274