This paper will propose an 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

The computational tools available for studying machine-readable corpora are at present still rather primitive. In the more advanced lexicographic organizations, there are concordancing programs (see figure below), which are basically KWIC (key word in context (Aho et al., 1988, p. 122), (Salton, 1989, p. 384)) indexes with additional features such as the ability to extend the context, sort leftwards as well as