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- Metaphor and the Communicative Mind by Brandt, Line
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Understanding Timelines: Conceptual Metaphor and Conceptual Integration
1Cognitive Science Dept. & Centre for Research in Language, UCSD
2Cognitive Science Dept., UCSD; Cognitive Science Dept., Case Western Reserve; Classics Dept., Universidad de Murcia
Citation Information: Cognitive Semiotics. Volume 5, Issue 1-2, Pages 198–219, ISSN (Online) 2235-2066, DOI: 10.1515/cogsem.2013.5.12.198, January 2014
- Published Online:
One of the most broadly investigated topics in the conceptual metaphor literature is the importance of spatial construals for thinking and talking about time. We address the relationship between conceptual metaphor theory (CMT) and conceptual integration theory (CIT) by exploring how people understand timelines - both as graphical objects, in discourse about timelines taken from newspapers and the web, and in poetic examples. The inferential structure of the timeline is well captured by the conceptual metaphors TIME IS SPACE and EVENTS ARE OBJECTS. Instantiated graphically, the timeline serves as a material anchor for a conceptual integration network representing partial cognitive models of time, lines, objects, and a hybrid model known as a ‘blend’. Understood in respect to this network, the analogue properties of the line give it novel computational properties facilitating inferences about the events that the timeline represents. The history of the modern timeline suggests that it reflects a distributed cognitive process, involving multiple individuals over a large span of time and illustrating the importance of cultural evolution in the development of conceptual integration networks. Analysis of both poetry and everyday discourse about timelines suggests that conventional mapping schemas are best viewed not as determining the interpretation of timelines but as providing soft constraints that help guide interpretation. Future metaphor research will best proceed via a merger of techniques from CMT and CIT, characterizing metaphor as involving complex networks of mappings that can be updated flexibly as a function of context and goals.