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
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