The clustering coefficient of phonological neighborhoods influences spoken word recognition

Abstract

Neighborhood density refers to the number of words, or neighbors, that are phonologically related to a given word. For example, the words BAT, MAT, CUT, and CAN (among others) are considered phonological neighbors of the word CAT. In contrast, the clustering coefficient of the neighborhood refers to the proportion of phonological neighbors that are also neighbors of each other. Among the neighbors of CAT, the words BAT and MAT are neighbors of each other, but the words BAT and CAN are not neighbors of each other. Despite the stimulus words having the same number of neighbors overall, the results of an auditory lexical decision task showed that words with a high clustering coefficient (i.e., most neighbors were also neighbors of each other) were responded to more quickly than words with a low clustering coefficient (i.e., few neighbors were also neighbors of each other). These results suggest that some aspects of phonological similarity (i.e., clustering coefficient) might facilitate lexical activation, whereas other aspects of phonological similarity (i.e., neighborhood density) influence a later, decision stage of processing characterized by competition among activated word-forms. [Work supported by NIH.]