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A graph theory model of the semantic structure of attitudes

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Abstract

The semantic structure underlying the attitudes of pretreatment and posttreatment drug addicts was modeled using a network analysis of free word associations. Measures of graph theoretic properties were used to assess structural differences in the associative networks of the two populations. These measures modeled the information processes of associative networks proposed in the spreading activation theory of semantic processing. As expected based on graph theory, the structure of the associative networks of post-treatment subjects was more dense, less constrained, and more hierarchically organized by the self concept. In a test of the network model, the subjects' evaluations of concepts in the associative network were found to be a function of their evaluations of semantically similar concepts. Although preliminary and limited, the results suggest that graph theory may provide a broad mathematical foundation for diverse models of cognitive systems.

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Authors and Affiliations

  1. University of Texas Medical Branch, 77550, Galveston, Texas

    Gregory Bovasso & Matthew Stanford

  2. Rapport, Inc., 20815, Chevy Chase, Maryland

    Lorand Szalay

Authors
  1. Gregory Bovasso
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  2. Lorand Szalay
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  3. Vincent Biase
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  4. Matthew Stanford
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The research was funded by a grant from the National Institute for Drug Abuse to the Institute of Cultural Studies, Inc.

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Bovasso, G., Szalay, L., Biase, V. et al. A graph theory model of the semantic structure of attitudes. J Psycholinguist Res 22, 411–425 (1993). https://doi.org/10.1007/BF01074344

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