Broadening the coverage of computational representations of metaphor through Dynamic Metaphor Theory

Current approaches to computational metaphor processing typically incorporate static representations of metaphor. We aim to show that this limits the coverage of such systems. We take insights from dynamic metaphor theory and discuss how existing computational models of metaphor might benefit from representing the dynamics of metaphor when applied to the analysis of conflicting discourse. We propose that a frame-based approach to metaphor representation based on the model of YinYang Dynamics of Metaphoricity (YYDM) would pave the way to more comprehensive modeling of metaphor. In particular, the metaphoricity cues of the YYDM model could be used to address the task of dynamic metaphor identification. Frame-based modeling of dynamic metaphor would facilitate the computational analysis of perspectives in conflicting discourse, with potential applications in analyzing political discourse.