In this contribution, we present a computational stylistic study and comparison of classic French literary texts based on a datadriven approach where discovering interesting linguistic patterns is done without any prior knowledge. We propose an objective measure capable of capturing and extracting meaningful stylistic syntactic patterns from a given author's work. Our hypothesis is based on the fact that the most relevant syntactic patterns should significantly reflect the author's stylistic choice and thus they should exhibit some kind of peculiar overrepresentation behavior controlled by the author's purpose with respect to a linguistic norm. The analyzed results show the effectiveness in extracting interesting syntactic patterns from novels, and seem particularly promising for the analysis of such particular texts.

A Peculiarity-based Exploration of Syntactical Patterns: a Computational Study of Stylistics

Francesca Frontini;
2015

Abstract

In this contribution, we present a computational stylistic study and comparison of classic French literary texts based on a datadriven approach where discovering interesting linguistic patterns is done without any prior knowledge. We propose an objective measure capable of capturing and extracting meaningful stylistic syntactic patterns from a given author's work. Our hypothesis is based on the fact that the most relevant syntactic patterns should significantly reflect the author's stylistic choice and thus they should exhibit some kind of peculiar overrepresentation behavior controlled by the author's purpose with respect to a linguistic norm. The analyzed results show the effectiveness in extracting interesting syntactic patterns from novels, and seem particularly promising for the analysis of such particular texts.
2015
Istituto di linguistica computazionale "Antonio Zampolli" - ILC
Computational Stylistics
Interestingness Measure
Sequential Pattern Mining
Syntactic Style
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/297255
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