在认知网络科学中用其他语言定义节点和边--超越单层网络

Information Pub Date : 2024-07-12 DOI:10.3390/info15070401
M. Vitevitch, Alysia E. Martinez, Riley England
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引用次数: 0

摘要

认知网络科学加深了我们对心理词汇结构以及这种结构在微观、中观和宏观层面如何影响语言和认知过程的理解。使用这种方法的研究大多使用单层英语单词网络。我们考虑了网络科学中的两个基本概念--节点和连接(或边缘)--在两种研究较少的语言(美国手语和卡奇克尔语)的背景下,看看单层网络是否能模拟这两种语言中单词之间的语音相似性。对这些单层网络的分析表明,网络结构存在若干差异,可能会对认知网络方法提出挑战。我们讨论了未来使用不同网络结构进行研究的几个方向,这些研究可以应对这些挑战,并加深我们对不同语言的语言处理可能存在的差异的理解。尽管人类语言之间存在差异,但这些工作也将为语言科学研究提供一个共同的框架。网络科学的方法论和理论工具还可以使我们更容易整合各种语言过程的研究,如典型和延迟发展、后天失调以及语音和语义信息的交互作用。最后,将认知网络科学方法与对英语以外语言的研究相结合,可能会进一步推动我们对认知过程的总体理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Defining Nodes and Edges in Other Languages in Cognitive Network Science—Moving beyond Single-Layer Networks
Cognitive network science has increased our understanding of how the mental lexicon is structured and how that structure at the micro-, meso-, and macro-levels influences language and cognitive processes. Most of the research using this approach has used single-layer networks of English words. We consider two fundamental concepts in network science—nodes and connections (or edges)—in the context of two lesser-studied languages (American Sign Language and Kaqchikel) to see if a single-layer network can model phonological similarities among words in each of those languages. The analyses of those single-layer networks revealed several differences in network architecture that may challenge the cognitive network approach. We discuss several directions for future research using different network architectures that could address these challenges and also increase our understanding of how language processing might vary across languages. Such work would also provide a common framework for research in the language sciences, despite the variation among human languages. The methodological and theoretical tools of network science may also make it easier to integrate research of various language processes, such as typical and delayed development, acquired disorders, and the interaction of phonological and semantic information. Finally, coupling the cognitive network science approach with investigations of languages other than English might further advance our understanding of cognitive processing in general.
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