A graph theory model of the semantic structure of attitudes

Gregory Bovasso, Lorand Szalay, Vincent Biase, Matthew S. Stanford

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)411-425
Number of pages15
JournalJournal of Psycholinguistic Research
Volume22
Issue number4
DOIs
StatePublished - Jul 1 1993

ASJC Scopus subject areas

  • Language and Linguistics
  • Experimental and Cognitive Psychology
  • Psychology(all)
  • Linguistics and Language

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