Vitevitch, Michael S.Ercal, GüneşAdagarla, Bhargav2016-09-082016-09-0820111664-1078http://hdl.handle.net/11413/1468Network science describes how entities in complex systems interact, and argues that the structure of the network influences processing. Clustering coefficient, C one measure of network structure refers to the extent to which neighbors of a node are also neighbors of each other. Previous simulations suggest that networks with low C dissipate information (or disease) to a large portion of the network, whereas in networks with high C information (or disease) tends to be constrained to a smaller portion of the network (Newman, 2003). In the present simulation we examined how C influenced the spread of activation to a specific node, simulating retrieval of a specific lexical item in a phonological network. The results of the network simulation showed that words with lower C had higher activation values (indicating faster or more accurate retrieval from the lexicon) than words with higher C. These results suggest that a simple mechanism for lexical retrieval can account for the observations made in Chan and Vitevitch (2009), and have implications for diffusion dynamics in other fields.en-USnetwork sciencesimulationclustering coefficientmental lexiconword recognitionağ bilimisimülasyonkümeleme katsayısızihinsel sözlüğükelime tanımaArticle2088638001832088638001832-s2.0-848622456052-s2.0-84862245605