Using complex networks to understand the mental lexicon

M. Vitevitch, Rutherford Goldstein, Cynthia S. Q. Siew, Nichol Castro
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引用次数: 18

Abstract

Abstract Network science is an emerging discipline drawing from sociology, computer science, physics and a number of other fields to examine complex systems in economical, biological, social, and technological domains. To examine these complex systems, nodes are used to represent individual entities, and links are used to represent relationships between entities, forming a web-like structure, or network, of the entire system. The structure that emerges in these complex networks influences the dynamics of that system. We provide a short review of how this mathematical approach has been used to examine the structure found in the phonological lexicon, and of how subsequent psycholinguistic investigations demonstrate that several of the structural characteristics of the phonological network influence various language-related processes, including word retrieval during the recognition and production of spoken words, recovery from instances of failed lexical retrieval, and the acquisition of word-forms. This approach allows researchers to examine the lexicon at the micro-, meso-, and macro-levels, holding much promise for increasing our understanding of language-related processes and representations.
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使用复杂的网络来理解心理词汇
网络科学是一门从社会学、计算机科学、物理学和许多其他领域发展起来的新兴学科,旨在研究经济、生物、社会和技术领域的复杂系统。为了检查这些复杂的系统,节点被用来表示单个实体,链接被用来表示实体之间的关系,形成整个系统的网状结构或网络。在这些复杂网络中出现的结构会影响系统的动态。我们简要回顾了如何使用这种数学方法来检查语音词汇中的结构,以及随后的心理语言学研究如何证明语音网络的几个结构特征影响各种语言相关过程,包括识别和产生口语单词时的单词检索,从失败的词汇检索中恢复,以及词形的习得。这种方法使研究人员能够在微观、中观和宏观层面上检查词汇,对增加我们对语言相关过程和表征的理解大有希望。
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