title: Spoken word recognition and serial recall of words from components in the phonological network.
abstract: Network science uses mathematical techniques to study complex systems such as the phonological lexicon (Vitevitch, 2008). The phonological network consists of a giant component (the largest connected component of the network) and lexical islands (smaller groups of words that are connected to each other, but not to the giant component). To determine if the component that a word resided in influenced lexical processing, language-related tasks (naming, lexical decision, and serial recall) were used to compare the processing of words from the giant component and from lexical islands. Results showed that words from lexical islands were recognized more quickly and recalled more accurately than words from the giant component. These findings can be accounted for via the diffusion of activation across a network. Implications for models of spoken word recognition and network science are also discussed.
authors: Department of Psychology, University of Kansas.
authors: Cynthia S Q
authors: CS
authors: Siew
authors: Department of Psychology, University of Kansas.
authors: Michael S
authors: MS
authors: Vitevitch
mesh_terms: D006801:Humans; D007807:Language Tests; D011939:Mental Recall; D046709:Pattern Recognition, Physiological; D011581:Psychological Tests; D011930:Reaction Time; D021641:Recognition, Psychology; D012044:Regression Analysis; D012691:Serial Learning; D013067:Speech Perception