Simulating retrieval from a highly clustered network: implications for spoken word recognition.
Front Psychol
; 2: 369, 2011.
Article
em En
| MEDLINE
| ID: mdl-22174705
ABSTRACT
Network 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.
Texto completo:
1
Base de dados:
MEDLINE
Idioma:
En
Ano de publicação:
2011
Tipo de documento:
Article