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Rhetorical Strategy in Forensic Speeches: Multidimensional Statistics-Based Methodology

Author

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  • Mónica Bécue-Bertaut
  • Belchin Kostov
  • Annie Morin
  • Guilhem Naro

Abstract

Rhetorical strategy is relevant in the law domain, where language is a vital instrument. Textual statistics have much to offer for uncovering such a strategy. We propose a methodology that starts from a non-structured text; first, the breakpoints are automatically detected and lexically homogeneous parts are identified; then, the shape of the text through the trajectory of these parts and their hierarchical structure are uncovered; finally, the argument flow is tracked along. Several methods are combined. Chronological clustering of multidimensional count series detects the breakpoints; the shape of the text is revealed by applying correspondence analysis to the parts×words table while the progression of the argument is described by labelled time-constrained hierarchical clustering. This methodology is illustrated on a rhetoric forensic application, concretely a closing speech delivered by a prosecutor at Barcelona Criminal Court. This approach could also be useful in politics, communication and professional writing. Copyright Springer Science+Business Media New York 2014

Suggested Citation

  • Mónica Bécue-Bertaut & Belchin Kostov & Annie Morin & Guilhem Naro, 2014. "Rhetorical Strategy in Forensic Speeches: Multidimensional Statistics-Based Methodology," Journal of Classification, Springer;The Classification Society, vol. 31(1), pages 85-106, April.
  • Handle: RePEc:spr:jclass:v:31:y:2014:i:1:p:85-106
    DOI: 10.1007/s00357-014-9148-9
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    Cited by:

    1. Marie Chavent & Vanessa Kuentz-Simonet & Amaury Labenne & Jérôme Saracco, 2018. "ClustGeo: an R package for hierarchical clustering with spatial constraints," Computational Statistics, Springer, vol. 33(4), pages 1799-1822, December.

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