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态度语义结构的图论模型。

A graph theory model of the semantic structure of attitudes.

作者信息

Bovasso G, Szalay L, Biase V, Stanford M

出版信息

J Psycholinguist Res. 1993 Jul;22(4):411-25. doi: 10.1007/BF01074344.

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 posttreatment 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.

摘要

通过对自由词联想进行网络分析,建立了治疗前和治疗后吸毒者态度背后的语义结构模型。使用图论属性度量来评估这两类人群联想网络中的结构差异。这些度量对语义加工的扩散激活理论中提出的联想网络信息过程进行了建模。正如基于图论所预期的那样,治疗后受试者的联想网络结构更密集、限制更少,并且由自我概念进行了更层次化的组织。在网络模型测试中,发现受试者对联想网络中概念的评价是他们对语义相似概念评价的一个函数。尽管结果初步且有限,但表明图论可能为认知系统的各种模型提供广泛的数学基础。

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