Purpose: Graph theory and the new science of networks provide a mathematically rigorous approach to examine the development and organization of complex systems. These tools were applied to the mental lexicon to examine the organization of words in the lexicon and to explore how that structure might influence the acquisition and retrieval of phonological word-forms. Method: Pajek, a program for large network analysis and visualization (V. Batagelj & A. Mvrar, 1998), was used to examine several characteristics of a network derived from a computerized database of the adult lexicon. Nodes in the network represented words, and a link connected two nodes if the words were phonological neighbors. Results: The average path length and clustering coefficient suggest that the phonological network exhibits small-world characteristics. The degree distribution was fit better by an exponential rather than a power-law function. Finally, the network exhibited assortative mixing by degree. Some of these structural characteristics were also found in graphs that were formed by 2 simple stochastic processes suggesting that similar processes might influence the development of the lexicon. Conclusions: The graph theoretic perspective may provide novel insights about the mental lexicon and lead to future studies that help us better understand language development and processing.

Two experiments using bisyllabic CVCCVC nonsense words that varied in phonotactic probability and stress placement were conducted to examine the influences of phonotactic and metrical information on spoken word recognition. Experiment 1 examined participants' intuitions about the phonological “goodness” of nonsense words. Experiment 2 examined processing times for the same stimuli in a speeded auditory repetition task. The results of both studies provide further evidence that the phonotactic configuration and stress placement of spoken stimuli have important implications for the representation and processing of spoken words.