Abstract
Semantic networks are often used to represent the meaning of a word in the mental lexicon. To construct a large-scale network for this lexicon, text corpora provide a convenient and rich resource. In this chapter the network properties of a text-based approach are evaluated and compared with a more direct way of assessing the mental content of the lexicon through word associations. This comparison indicates that both approaches highlight different properties specific to linguistic and mental representations. Both types of network are qualitatively different in terms of their global network structure and the content of the network communities. Moreover, behavioral data from relatedness judgments show that language networks do not capture these judgments as well as mental networks.
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De Deyne, S., Verheyen, S., Storms, G. (2016). Structure and Organization of the Mental Lexicon: A Network Approach Derived from Syntactic Dependency Relations and Word Associations. In: Mehler, A., Lücking, A., Banisch, S., Blanchard, P., Job, B. (eds) Towards a Theoretical Framework for Analyzing Complex Linguistic Networks. Understanding Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47238-5_3
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