title: Word associations: network and semantic properties.
abstract: A number of properties of word associations, generated in a continuous task, were investigated. First, we investigated the correspondence of word class in association cues and responses. Nouns were the modal word class response, regardless of the word class of the cue, indicating a dominant paradigmatic response style. Next, the word association data were used to build an associative network to investigate the centrality of nodes. The study of node centrality showed that central nodes in the network tended to be highly frequent and acquired early. Small-world properties of the association network were investigated and compared with a large English association network (Steyvers & Tenenbaum, 2005). Networks based on a multiple association procedure showed small-world properties despitebeing denser than networks based on a discrete task. Finally, a semantic taxonomy was used to investigate the composition of semantic types in association responses. The majority of responses were thematically related situation responses and entity responses referring to parts, shape, or color. Since the association task required multiple responses per cue, the interaction between generation position and semantic role could be investigated and discussed in the framework of recent theories of natural concept representations (Barsalou, Santos, Simmons, & Wilson, in press).
authors.affiliation: Department of Psychologie, University of Leuven, Leuven, Belgium. simon.dedeyne@psy.kuleuven.be
authors.forename: Simon
authors.initials: S
authors.lastname: De Deyne
authors.forename: Gert
authors.initials: G
authors.lastname: Storms
mesh_terms: D000465:Algorithms; D003463:Cues; D005502:Food; D006801:Humans; D012660:Semantics; D014936:Word Association Tests