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English semantic feature production norms: An extended database of 4436 concepts.
Buchanan, Erin M; Valentine, K D; Maxwell, Nicholas P.
Afiliação
  • Buchanan EM; Harrisburg University of Science and Technology, 326 Market St, Harrisburg, PA, 17101, USA. ebuchanan@harrisburgu.edu.
  • Valentine KD; Harvard Medical School - Division of General Internal Medicine, Massachusetts General Hospital, 275 Cambridge St, Boston, MA, 02114, USA.
  • Maxwell NP; University of Southern Mississippi, Hattiesburg, MS, 39406, USA.
Behav Res Methods ; 51(4): 1849-1863, 2019 08.
Article em En | MEDLINE | ID: mdl-31044359
ABSTRACT
A limiting factor in understanding memory and language is often the availability of large numbers of stimuli to use and explore in experimental studies. In this study, we expand on three previous databases of concepts to over 4000 words including nouns, verbs, adjectives, and other parts of speech. Participants in the study were asked to provide lists of features for each concept presented (a semantic feature production task), which were combined with previous research in this area. These feature lists for each concept were then coded into their root word form and affixes (i.e., cat and s for cats) to explore the impact of word form on semantic similarity measures, which are often calculated by comparing concept feature lists (feature overlap). All concept features, coding, and calculated similarity information is provided in a searchable database for easy access and utilization for future researchers when designing experiments that use word stimuli. The final database of word pairs was combined with the Semantic Priming Project to examine the relation of semantic similarity statistics on semantic priming in tandem with other psycholinguistic variables.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Semântica / Bases de Dados Factuais Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Semântica / Bases de Dados Factuais Idioma: En Ano de publicação: 2019 Tipo de documento: Article