The semantics of metaphor

Introductory course, in the Logic and Language area at the 32nd European Summer School in Logic, Language and Information, 26-30 July 2021

Metaphor is a pervasive factor in natural language, underlying the conscious creation of verbal images (e.g., brexit as a divorce), but also the flexibility of our most basic vocabulary (like prepositions). The nature of metaphors (as mappings between conceptual domains) has been the constant concern of cognitive linguistics and psychologist since the eighties and there is a booming interest in detecting them in texts using computational techniques. Interestingly, there is hardly any formal semantic work on metaphors (e.g. their compositionality), which obviously hampers a full understanding of how metaphor works. This course provides a broad introduction to the study of metaphors: how they are defined, analyzed as mappings, identified in corpora, represented in databases, formalized in semantic and pragmatic theories. This will enable students to find their way in this large area and to contribute, from their own area of expertise, to the development of a full-fledged semantics of metaphor.

Metaphor is an interdisciplinary field of research, interfacing with cognition and computation (Glucksberg & Keysar 1990, Gentner & Bowdle 2008, Goguen 1999, Shutova 2015). It is theoretically relevant, for what it reveals about the way meaning is made, not only in language (from lexicon to discourse, Lakoff & Johnson 1980), but also in other domains (e.g. in mathematics, Guhe et al. 2009). It is also practically relevant for lexicography, digital humanities (Anderson et al. 2016), and natural language processing (Shutova 2015).

There are rapid new developments in the research on metaphor. Large metaphor repositories are build, visualized, and exploited empirically and practically (Mapping Metaphor 2015, Dodge et al. 2015). The structure notions of conceptal frames and syntactic constructions are being formalized and systematically applied to metaphors (Sullivan 2013, Stickles et al. 2016). Kao et al. (2014) test the application of a probabilistic pragmatic model to metaphor. Experimental methods put specific metaphor theories to the test (Pouscoulous & Dulcinati 2019). In the computational domain there is a surge of new work on (automatic) metaphor detection (Shutova 2015).

At the same time the contribution of formal (truth-conditional, model-theoretic, logic-oriented) semantics to this field is very limited, leaving a large gap right in the middle of it. It is exactly formal semantics which has the potential to connect many of the different corners of current research in the domain of metaphor, because (among other things) of its commitment to compositionality, its well-proven formal toolkit, and its attention to the way semantics interfaces with lexicon, pragmatics, and discourse.

This course does not have the ambition to fill this gap or to teach a unique formal semantic theory of metaphor that has the potential to fill it. The goal is to introduce students with different backgrounds to the present state of the field (including this gap) and to show where the different possible connections are for anyone interested in contributing to the semantics of metaphor.

The course requires only elementary knowledge of linguistic and logical notions as can be learned from introductory courses in linguistics, semantics, and logic.

1 The definition of metaphor

The characterization of metaphor in the wider linguistic, cognitive, and computational context of figurative language (Dancygier & Sweetser 2014), analogy (Gentner & Bowdle 2008), categorization (Glucksberg & Keysar 1990), mapping (Goguen 1999). See also Zwarts (2019).

Slides 1

2 The analysis of metaphor

Analyzing metaphor: The analysis of metaphor as mappings between domains, starting with conceptual metaphor theory (Lakoff & Johnson 1980) and conceptual blending theory (Fauconnier & Turner 2002). See also Zwarts (2019).

Slides 2

3 The identification of metaphor

The identification of metaphors in corpora, involving procedures for annotation (e.g., Pragglejaz 2007) but also by various computational methods (e.g., Shutova 2016). See also Zwarts (2020).

Slides 3

4 The representation of metaphor

Large-scale repositories of metaphors and their visualization, in MetaNet and in the Metaphor Map of English (Mapping Metaphor 2015), based on semantic domains, and its use of these in the discovery of large-scale patterns (Xu et al. 2017). See also Zwarts (2020).

Slides 4

5 The formalization of metaphor

Aspects of the formalization of metaphors, including the role of frames (Stickles et al. 2016), the application to mathematics (Guhe et al. 2009) and the use of conversational principles (Kao et al. 2014). See also Zwarts (2018).

Slides 5

References

Anderson, W., Bramwell, E., & Hough, C. (2016). Mapping English Metaphor Through Time. Oxford: Oxford University Press.

Dancygier, B., & Sweetser, E. (2014). Figurative Language. Cambridge: Cambridge University Press.

Dodge, E., Hong, J., & Stickles, E. (2015). MetaNet: Deep semantic automatic metaphor analysis. Proceedings of the Third Workshop on Metaphor in NLP, 40–49.

Fauconnier, G., & Turner, M. (2002). The Way We Think: Conceptual Blending and the Mind’s Hidden Complexities. Basic Books.

Gentner, D., & Bowdle, B. (2008). Metaphor as structure-mapping. In R. W. Gibbs, Jr., (Ed.), Cambridge handbook of metaphor and thought (pp. 109 –128). New York, NY: Cambridge University Press.

Glucksberg, S., & Keysar, B. (1990). Understanding metaphorical comparisons: Beyond similarity. Psychological Review, 97, 3–18.

Goguen, J. (1999). An introduction to algebraic semiotics, with application to user interface design. In C. Nehaniv (Ed.), Computation for metaphors, analogy, and agents (pp. 242–291). Berlin: Springer.

Guhe, M., Smaill, A., & Pease, A. (2009). A Formal Cognitive Model of Mathematical Metaphors. In B. Mertsching, M. Hund, & Z. Aziz (Eds.), KI 2009: Advances in Artificial Intelligence (pp. 323–330). Springer Berlin Heidelberg.

Kao, J. T., Bergen, L., & Goodman, N. D. (2014). Formalizing the pragmatics of metaphor understanding. Proceedings of the 36th Annual Meeting of the Cognitive Science Society, 719–724. Wheat Ridge, CO: Cognitive Science Society.

Mapping Metaphor with the Historical Thesaurus (2015). Metaphor Map of English Glasgow: University of Glasgow. http://mappingmetaphor.arts.gla.ac.uk.

Lakoff, G., & Johnson, M. (1980). Metaphors We Live By. Chicago: University of Chicago Press.

Pouscoulous, N., & G. Dulcinati (2019). Metaphor. In C. Cummins & N. Katsos (Eds.), The Oxford Handbook of Experimental Semantics and Pragmatics (pp. 298-315). Oxford: Oxford University Press.

Pragglejaz Group. (2007). MIP: A Method for Identifying Metaphorically Used Words in Discourse. Metaphor and Symbol, 22(1), 1–39.

Shutova, E. (2015). Design and Evaluation of Metaphor Processing Systems. Computational Linguistics, 41(4), 579–623.

Stickles, E., David, O., Dodge, E. K., & Hong, J. (2016). Formalizing contemporary conceptual metaphor theory. Constructions and Frames, 8(2), 166–213.

Sullivan, K. (2013). Frames and constructions in metaphoric language. Amsterdam/Philadelphia: John Benjamins.

Xu, Y., Malt, B. C., & Srinivasan, M. (2017). Evolution of word meanings through metaphorical mapping: Systematicity over the past millennium. Cognitive Psychology, 96, 41–53.

Zwarts, J. (2018). Rising temperatures and other paths. Handout for presentation at ENDPOINTS 2018: Endpoints, scales, and results in the decomposition of verbal predicates. Humboldt Universität, Berlin, 30 January.

Zwarts, J. (2019). On domain adjectives and the metaphors they modify. In Julian J. Schlöder, Dean McHugh & Floris Roelofsen (Eds.), Proceedings of the 22nd Amsterdam Colloquium (pp 437-444). Amsterdam: ILLC.

Zwarts, J. (2020). Mining and mapping New Testament metaphors and the Louw-Nida lexicon. Ms. Utrecht University.