Word association norms, mutual information, and lexicography

  • Authors:

  • Kenneth Ward Church;Patrick Hanks

  • Affiliations:

  • Bell Laboratories, Murray Hill, N.J.;Collins Publishers, Glasgow, Scotland

  • Venue:
  • ACL '89 Proceedings of the 27th annual meeting on Association for Computational Linguistics
  • Year:
  • 1989

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Abstract

The term word association is used in a very particular sense in the psycholinguistic literature. (Generally speaking, subjects respond quicker than normal to the word "nurse" if it follows a highly associated word such as "doctor.") We will extend the term to provide the basis for a statistical description of a variety of interesting linguistic phenomena, ranging from semantic relations of the doctor/nurse type (content word/content word) to lexico-syntactic co-occurrence constraints between verbs and prepositions (content word/function word). This paper will propose a new objective measure based on the information theoretic notion of mutual information, for estimating word association norms from computer readable corpora. (The standard method of obtaining word association norms, testing a few thousand subjects on a few hundred words, is both costly and unreliable.) The proposed measure, the association ratio, estimates word association norms directly from computer readable corpora, making it possible to estimate norms for tens of thousands of words.