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Mining for characterising patterns in literature using correspondence analysis: an experiment on French novels.

This paper presents and describes a bottom-up methodology for the detection of stylistic traits in the syntax of literary texts. The extraction of syntactic patterns is performed blindly by a sequential pattern mining algorithm, while the identification of significant and interesting features is per...

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Published in:DHQ: Digital Humanities Quarterly Vol. 11; no. 2; pp. 131 - 145
Main Authors: Frontini, Francesca, Boukhaled, Mohamed Amine, Ganascia, Jean-Gabriel
Format: Article
Published: Digital Humanities Quarterly 2017
Subjects:
Literature
French fiction
Linguistics
Normalization (Sociology)
Social theory
Online Access:View this record in EBSCOhost
Summary:This paper presents and describes a bottom-up methodology for the detection of stylistic traits in the syntax of literary texts. The extraction of syntactic patterns is performed blindly by a sequential pattern mining algorithm, while the identification of significant and interesting features is performed at a later stage by using correspondence analysis and by ranking patterns by contribution.