title: The role of corpus size and syntax in deriving lexico-semantic representations for a wide range of concepts.
abstract: One of the most significant recent advances in the study of semantic processing is the advent of models based on text and other corpora. In this study, we address what impact both the quantitative and qualitative properties of corpora have on mental representations derived from them. More precisely, we evaluate models with different linguistic and mental constraints on their ability to predict semantic relatedness between items from a vast range of domains and categories. We find that a model based on syntactic dependency relations captures significantly less of the variability for all kinds of words, regardless of the semantic relation between them or their abstractness. The largest difference was found for concrete nouns, which are commonly used to assess semantic processing. For both models we find that limited amounts of data suffice in order to obtain reliable predictions. Together, these findings suggest new constraints for the construction of mental models from corpora, both in terms of the corpus size and in terms of the linguistic properties that contribute to mental representations.
authors.affiliation: a Department of Psychology , University of Leuven , Belgium.
authors.forename: Simon
authors.initials: S
authors.lastname: De Deyne
authors.forename: Steven
authors.initials: S
authors.lastname: Verheyen
authors.forename: Gert
authors.initials: G
authors.lastname: Storms
mesh_terms: D001244:Association; D003210:Concept Formation / Q000502:physiology*; D066264:Datasets as Topic; D005260:Female; D006801:Humans; D007802:Language; D008297:Male; D008606:Mental Processes / Q000502:physiology*; D008960:Models, Psychological; D012044:Regression Analysis; D012660:Semantics; D014825:Vocabulary
keywords: Semantic memory; Similarity; Syntactic dependency; Text corpora; Word associations