Semantic Map Geometry: Two Approaches

Abstract

This paper discusses two ways in which the geometry of a semantic map can be defined: on the basis of a set of cross-linguistic data or on the basis of a semantic analysis of the meanings involved. I will argue that under a purely " data-driven " approach certain important aspects of contiguity in semantic maps, like exceptions and family resemblance structure, remain unclear and that we can get more insight into these aspects when working from a semantically defined geometry. The two approaches can complement each other in the use of semantic maps. A semantic map is a ―spatial‖ representation of the ways in which a set of linguistic meanings hangs together. More similar meanings are closer together on the map, while less similar meanings are further apart. Underlying the spatial representation is a particular geometry that defines how similarities correspond to spatial distances or connections, either in graphs or in MDS. This paper is about two different ways in which the geometry of a semantic map can be derived and applied, working from cross-linguistic data or working from a semantic model. Because these two approaches both have their limitations, it follows that they can complement, inform, and correct each other. After a brief introduction to the notion of semantic maps in section 1, I will explain the two approaches in section 2 and some of the limitations and pitfalls in section 3 and section 4. Section 5 concludes the paper.