Siew Cynthia S Q, Vitevitch Michael S
Department of Psychology, University of Kansas.
J Exp Psychol Learn Mem Cogn. 2016 Mar;42(3):394-410. doi: 10.1037/xlm0000139. Epub 2015 Aug 24.
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.
网络科学运用数学技术来研究诸如语音词汇这类复杂系统（维特维奇，2008）。语音网络由一个巨型组件（网络中最大的连通组件）和词汇孤岛（相互连接但不与巨型组件相连的较小单词组）组成。为了确定单词所在的组件是否会影响词汇处理，研究者使用了与语言相关的任务（命名、词汇判断和系列回忆）来比较巨型组件和词汇孤岛中单词的处理情况。结果表明，与巨型组件中的单词相比，词汇孤岛中的单词被识别得更快，回忆得也更准确。这些发现可以通过激活在网络中的扩散来解释。文中还讨论了对口语单词识别模型和网络科学的启示。
