Computational Exploration of Metaphor Comprehension Processes

A central question in metaphor research is what processes are involved in metaphor comprehension, especially which of comparison and categorization processes governs metaphor comprehension. In this paper, I attempt to provide a computational solution to this problem using comparison and categorization algorithms based on word vectors in a multidimensional semantic space constructed by latent semantic analysis. These algorithms receive word vectors for the topic and the vehicle of a metaphor and compute a vector for the metaphorical meaning. The resulting vectors can be evaluated on the degree to which they mimic human interpretation of the same metaphor. Using this simulation framework, I tested five competing views of metaphor comprehension: the categorization view (Glucksberg, 2001), the comparison view (Gentner, 1983) and three hybrid views — the conventionality view (Bowdle & Gentner, 2005), the aptness view (Jones & Estes, 2005) and the interpretive diversity view (Utsumi & Kuwabara, 2005) — which claim that vehicle conventionality, aptness and interpretive diversity, respectively, determine a shift between both processes. The simulation result was that the interpretive diversity view outperformed the other four views on two different measures. This result can be seen as computational evidence in favor of the interpretive diversity view.