Patterns of local discourse coherence as a feature for authorship attribution.

We define a model of discourse coherence based on Barzilay and Lapata’s entity grids as a stylometric feature for authorship attribution. Unlike standard lexical and character-level features, it operates at a discourse (cross-sentence) level. We test it against and in combination with standard featu...

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Bibliographic Details
Published in:Literary & Linguistic Computing Vol. 29; no. 2; pp. 191 - 199
Main Authors: Feng, Vanessa Wei, Hirst, Graeme
Format: Article
Published: Oxford University Press / USA Jun2014
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Online Access:View this record in EBSCOhost
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Summary:We define a model of discourse coherence based on Barzilay and Lapata’s entity grids as a stylometric feature for authorship attribution. Unlike standard lexical and character-level features, it operates at a discourse (cross-sentence) level. We test it against and in combination with standard features on nineteen book-length texts by nine nineteenth-century authors. We find that coherence alone performs often as well as and sometimes better than standard features, though a combination of the two has the highest performance overall. We observe that despite the difference in levels, there is a correlation in performance of the two kinds of features.