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• W2897879535 startingPage "2890" @default.
• W2897879535 abstract "The contents and structure of semantic memory have been the focus of much recent research, with major advances in the development of distributional models, which use word co-occurrence information as a window into the semantics of language. In parallel, connectionist modeling has extended our knowledge of the processes engaged in semantic activation. However, these two lines of investigation have rarely been brought together. Here, we describe a processing model based on distributional semantics in which activation spreads throughout a semantic network, as dictated by the patterns of semantic similarity between words. We show that the activation profile of the network, measured at various time points, can successfully account for response times in lexical and semantic decision tasks, as well as for subjective concreteness and imageability ratings. We also show that the dynamics of the network is predictive of performance in relational semantic tasks, such as similarity/relatedness rating. Our results indicate that bringing together distributional semantic networks and spreading of activation provides a good fit to both automatic lexical processing (as indexed by lexical and semantic decisions) as well as more deliberate processing (as indexed by ratings), above and beyond what has been reported for previous models that take into account only similarity resulting from network structure." @default.
• W2897879535 created "2018-10-26" @default.
• W2897879535 creator A5024406485 @default.
• W2897879535 creator A5035859155 @default.
• W2897879535 creator A5076704114 @default.
• W2897879535 date "2018-10-07" @default.
• W2897879535 modified "2023-10-17" @default.
• W2897879535 title "Modeling the Structure and Dynamics of Semantic Processing" @default.
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• W2897879535 doi "https://doi.org/10.1111/cogs.12690" @default.
• W2897879535 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6585957" @default.
• W2897879535 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30294932" @default.
• W2897879535 hasPublicationYear "2018" @default.
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