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Evaluation of Measures of Distinctiveness. Classification of Literary Texts on the Basis of Distinctive Words

Du, Keli ; Dudar, Julia ; Schöch, Christof (2022)
Evaluation of Measures of Distinctiveness. Classification of Literary Texts on the Basis of Distinctive Words.
In: Journal of Computational Literary Studies, 1 (1)
doi: 10.48694/jcls.102
Artikel, Bibliographie

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Kurzbeschreibung (Abstract)

This paper concerns an empirical evaluation of nine different measures of distinctiveness or ‘keyness’ in the context of Computational Literary Studies. We use nine different sets of literary texts (specifically, novels) written in seven different languages as a basis for this evaluation. The evaluation is performed as a downstream classification task, where segments of the novels need to be classified by subgenre or period of first publication. The classifier receives different numbers of features identified using different measures of distinctiveness. The main contribution of our paper is that we can show that across a wide variety of parameters, but especially when only a small number of features is used, (more recent) dispersion-based measures very often outperform other (more established) frequency-based measures by significant margins. Our findings support an emerging trend to consider dispersion as an important property of words in addition to frequency.

Typ des Eintrags: Artikel
Erschienen: 2022
Autor(en): Du, Keli ; Dudar, Julia ; Schöch, Christof
Art des Eintrags: Bibliographie
Titel: Evaluation of Measures of Distinctiveness. Classification of Literary Texts on the Basis of Distinctive Words
Sprache: Englisch
Publikationsjahr: 2022
Ort: Darmstadt
Verlag: Universitäts- und Landesbibliothek Darmstadt
Titel der Zeitschrift, Zeitung oder Schriftenreihe: Journal of Computational Literary Studies
Jahrgang/Volume einer Zeitschrift: 1
(Heft-)Nummer: 1
Kollation: 21 Seiten
DOI: 10.48694/jcls.102
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Kurzbeschreibung (Abstract):

This paper concerns an empirical evaluation of nine different measures of distinctiveness or ‘keyness’ in the context of Computational Literary Studies. We use nine different sets of literary texts (specifically, novels) written in seven different languages as a basis for this evaluation. The evaluation is performed as a downstream classification task, where segments of the novels need to be classified by subgenre or period of first publication. The classifier receives different numbers of features identified using different measures of distinctiveness. The main contribution of our paper is that we can show that across a wide variety of parameters, but especially when only a small number of features is used, (more recent) dispersion-based measures very often outperform other (more established) frequency-based measures by significant margins. Our findings support an emerging trend to consider dispersion as an important property of words in addition to frequency.

Freie Schlagworte: keyness, evaluation, literary texts, distinctiveness
Zusätzliche Informationen:

Urspr. Konferenzveröffentlichung/Originally conference publication: 1st Annual Conference of Computational Literary Studies, 01.-02.06.2022, Darmstadt, Germany

Sachgruppe der Dewey Dezimalklassifikatin (DDC): 800 Literatur > 800 Literatur, Rhetorik, Literaturwissenschaft
Fachbereich(e)/-gebiet(e): 02 Fachbereich Gesellschafts- und Geschichtswissenschaften > Institut für Sprach- und Literaturwissenschaft > Digital Philology - Neuere deutsche Literaturwissenschaft
02 Fachbereich Gesellschafts- und Geschichtswissenschaften
02 Fachbereich Gesellschafts- und Geschichtswissenschaften > Institut für Sprach- und Literaturwissenschaft
Hinterlegungsdatum: 02 Aug 2024 12:49
Letzte Änderung: 02 Aug 2024 12:49
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