Computational Exploration of Metaphor Comprehension Processes Using a Semantic Space Model
Article first published online: 8 NOV 2010
Copyright © 2010 Cognitive Science Society, Inc.
Volume 35, Issue 2, pages 251–296, March 2011
How to Cite
Utsumi, A. (2011), Computational Exploration of Metaphor Comprehension Processes Using a Semantic Space Model. Cognitive Science, 35: 251–296. doi: 10.1111/j.1551-6709.2010.01144.x
- Issue published online: 10 FEB 2011
- Article first published online: 8 NOV 2010
- Received 22 October 2008; received in revised form 25 June 2010; accepted 26 July 2010
- Metaphor comprehension;
- Cognitive modeling;
- Semantic space model;
- Latent semantic analysis (LSA);
- Interpretive diversity;
- Maximum likelihood estimation
Recent metaphor research has revealed that metaphor comprehension involves both categorization and comparison processes. This finding has triggered the following central question: Which property determines the choice between these two processes for metaphor comprehension? Three competing views have been proposed to answer this question: the conventionality view (Bowdle & Gentner, 2005), aptness view (Glucksberg & Haught, 2006b), and interpretive diversity view (Utsumi, 2007); these views, respectively, argue that vehicle conventionality, metaphor aptness, and interpretive diversity determine the choice between the categorization and comparison processes. This article attempts to answer the question regarding which views are plausible by using cognitive modeling and computer simulation based on a semantic space model. In the simulation experiment, categorization and comparison processes are modeled in a semantic space constructed by latent semantic analysis. These two models receive word vectors for the constituent words of a metaphor and compute a vector for the metaphorical meaning. The resulting vectors can be evaluated according to the degree to which they mimic the human interpretation of the same metaphor; the maximum likelihood estimation determines which of the two models better explains the human interpretation. The result of the model selection is then predicted by three metaphor properties (i.e., vehicle conventionality, aptness, and interpretive diversity) to test the three views. The simulation experiment for Japanese metaphors demonstrates that both interpretive diversity and vehicle conventionality affect the choice between the two processes. On the other hand, it is found that metaphor aptness does not affect this choice. This result can be treated as computational evidence supporting the interpretive diversity and conventionality views.