Semantic Maps and Multidimensional Scaling

2012 ◽

Vol 3 (1) ◽

pp. 209-225

Author(s):

Andres Karjus

Keyword(s):

Natural Language ◽

Multidimensional Scaling ◽

Language Change ◽

Statistical Modelling ◽

Language Community ◽

Exterior Region ◽

Semantic Maps ◽

Closed Class ◽

Modelling Method ◽

The Baltic

The change of a lexical element into a grammatical (closed class) element must necessarily include intermediary stages where the element is considered gradually less lexical and more grammatical. The central assumptions in this study are the gradualness and gradience of grammaticalization, that natural language change cannot happen overnight, and that the change is driven by individual speakers of a language community (cf. Traugott and Trousdale 2010: 23, 26). Using a data sample from a questionnaire on spatial grams of the EXTERIOR-REGION (cf. Svorou 1994) in Estonian, Võro and Latvian, an attempt is made to model diachronic gradualness through synchronic gradience. The analysis and the explication thereof are carried out using multidimensional scaling, a statistical modelling method used akin to semantic maps.

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Generating semantic maps through multidimensional scaling: linguistic applications and theory

Corpus Linguistics and Linguistic Theory ◽

10.1515/cllt-2021-0018 ◽

2022 ◽

Vol 0 (0) ◽

Author(s):

Martijn van der Klis ◽

Jos Tellings

Keyword(s):

Multidimensional Scaling ◽

Past Research ◽

Statistical Technique ◽

Theoretical Frameworks ◽

Parallel Corpus ◽

Semantic Maps ◽

Research Questions ◽

Is Theory ◽

Corpus Data ◽

Mathematical Foundations

Abstract This paper reports on the state-of-the-art in application of multidimensional scaling (MDS) techniques to create semantic maps in linguistic research. MDS refers to a statistical technique that represents objects (lexical items, linguistic contexts, languages, etc.) as points in a space so that close similarity between the objects corresponds to close distances between the corresponding points in the representation. We focus on the use of MDS in combination with parallel corpus data as used in research on cross-linguistic variation. We first introduce the mathematical foundations of MDS and then give an exhaustive overview of past research that employs MDS techniques in combination with parallel corpus data. We propose a set of terminology to succinctly describe the key parameters of a particular MDS application. We then show that this computational methodology is theory-neutral, i.e. it can be employed to answer research questions in a variety of linguistic theoretical frameworks. Finally, we show how this leads to two lines of future developments for MDS research in linguistics.

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