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Simulating Retrieval From A Highly Clustered Network: Implications For Spoken Word Recognition

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Author
Vitevitch, Michael S.
Ercal, Güneş
Adagarla, Bhargav
Type
Article
Date
2011
Language
en_US
Metadata
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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.
Subject
network science
simulation
clustering coefficient
mental lexicon
word recognition
ağ bilimi
simülasyon
kümeleme katsayısı
zihinsel sözlüğü
kelime tanıma
URI
http://hdl.handle.net/11413/1468
Collections
  • Makaleler / Articles [100]
  • Scopus Publications [724]
  • WoS Publications [1016]

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İstanbul Kültür University

Hakkında |Politika | Kütüphane | İletişim | Send Feedback | Admin

Istanbul Kültür University, Ataköy Campus E5 Karayolu Üzeri Bakırköy 34158, İstanbul / TURKEY
Copyright © İstanbul Kültür University

Creative Commons Lisansı
IKU Institutional Repository, Creative Commons Alıntı-GayriTicari-Türetilemez 4.0 Uluslararası Lisansı ile lisanslanmıştır.

Designed by  UNIREPOS