A statistical method for the identification and aggregation of regional linguistic variation

Author:

Grieve Jack,Speelman Dirk,Geeraerts Dirk

Abstract

AbstractThis paper introduces a method for the analysis of regional linguistic variation. The method identifies individual and common patterns of spatial clustering in a set of linguistic variables measured over a set of locations based on a combination of three statistical techniques: spatial autocorrelation, factor analysis, and cluster analysis. To demonstrate how to apply this method, it is used to analyze regional variation in the values of 40 continuously measured, high-frequency lexical alternation variables in a 26-million-word corpus of letters to the editor representing 206 cities from across the United States.

Publisher

Cambridge University Press (CUP)

Subject

Linguistics and Language,Education,Language and Linguistics

Reference63 articles.

1. Wieling Martijn , & Nerbonne John . (2010). Hierarchical bipartite spectral graph partitioning to cluster dialect varieties and determine their most important linguistic features. Paper presented at: TextGraphs-5 Workshop on Graph-Based Methods for Natural Language Processing 16, July 16, 2010, Uppsala, Sweden. 33–41.

2. American Regional Dialects

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