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Computational Linguistics and Intelligent Text Processing

Volume 5449 of the series Lecture Notes in Computer Science pp 594-602

Linguistic Ethnography: Identifying Dominant Word Classes in Text

  • Rada MihalceaAffiliated withComputer Science Department, University of North TexasComputational Linguistics Group, Oxford University
  • , Stephen PulmanAffiliated withComputational Linguistics Group, Oxford University

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Abstract

In this paper, we propose a method for ”linguistic ethnography” – a general mechanism for characterising texts with respect to the dominance of certain classes of words. Using humour as a case study, we explore the automatic learning of salient word classes, including semantic classes (e.g., person, animal), psycholinguistic classes (e.g., tentative, cause), and affective load (e.g., anger, happiness). We measure the reliability of the derived word classes and their associated dominance scores by showing significant correlation across different corpora.