Word association norms, mutual information, and lexicography

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.

Abstract

The term word assaciation 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 wilt 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, waki,~g it possible to estimate norms for tens of thousands of words. I. Meaning and AssociationIt is common practice in linguistics to classify words not only on the basis of their meanings but also on the basis of their co-occurrence with other words.Running through the whole Firthian tradition, for example, is the theme that "You shall know a word by the company it keeps" (Firth, 1957)."On the one hand, bank ¢o.occors with words and expression such u money, nmu.loan, account, ~m.c~z~c.o~.ctal, manager, robbery, vaults, wortln# in a, lu action, Fb~Nadonal. of F.ngland, and so forth.On the other hand, we find bank m-occorring with r~r.~bn, boa:.am (end