Checking and bootstrapping lexical norms by means of word similarity indexes

In psychology, lexical norms related to the semantic properties of words, such as concreteness and valence, are important research resources. Collecting such norms by asking judges to rate the words is very time consuming, which strongly limits the number of words that compose them. In the present article, we present a technique for estimating lexical norms based on the latent semantic analysis of a corpus. The analyses conducted emphasize the technique's effectiveness for several semantic dimensions. In addition to the extension of norms, this technique can be used to check human ratings to identify words for which the rating is very different from the corpus-based estimate.