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  1. Modeling the Structure and Dynamics of Semantic Processing.Armand S. Rotaru, Gabriella Vigliocco & Stefan L. Frank - 2018 - Cognitive Science 42 (8):2890-2917.
    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, (...)
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  • Graph‐Theoretic Properties of Networks Based on Word Association Norms: Implications for Models of Lexical Semantic Memory.Thomas M. Gruenenfelder, Gabriel Recchia, Tim Rubin & Michael N. Jones - 2016 - Cognitive Science 40 (6):1460-1495.
    We compared the ability of three different contextual models of lexical semantic memory and of a simple associative model to predict the properties of semantic networks derived from word association norms. None of the semantic models were able to accurately predict all of the network properties. All three contextual models over-predicted clustering in the norms, whereas the associative model under-predicted clustering. Only a hybrid model that assumed that some of the responses were based on a contextual model and others on (...)
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  • Feature Statistics Modulate the Activation of Meaning During Spoken Word Processing.Barry J. Devereux, Kirsten I. Taylor, Billi Randall, Jeroen Geertzen & Lorraine K. Tyler - 2016 - Cognitive Science 40 (2):325-350.
    Understanding spoken words involves a rapid mapping from speech to conceptual representations. One distributed feature-based conceptual account assumes that the statistical characteristics of concepts’ features—the number of concepts they occur in and likelihood of co-occurrence —determine conceptual activation. To test these claims, we investigated the role of distinctiveness/sharedness and correlational strength in speech-to-meaning mapping, using a lexical decision task and computational simulations. Responses were faster for concepts with higher sharedness, suggesting that shared features are facilitatory in tasks like lexical decision (...)
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