Corpus-based Dialectometry: Aggregate Morphosyntactic Variability in British English Dialects

Abstract

The research reported in this paper departs from most previous work in dialectometry in several ways. Empirically, it draws on frequency vectors derived from naturalistic corpus data and not on discrete atlas classifications. Linguistically, it is concerned with morphosyntactic (as opposed to lexical or pronunciational) variability. Methodologically, it marries the careful analysis of dialect phenomena in authentic, naturalistic texts to aggregational-dialectometrical techniques. Two research questions guide the investigation: First, on methodological grounds, is corpus-based dialectometry viable at all? Second, to what extent is morphosyntactic variation in non-standard British dialects patterned geographically? By way of validation, findings will be matched against previous work on the dialect geography of Great Britain.

A comparison of statistical methods for the aggregation of regional linguistic variation

“…Before generating a linguistic distance matrix, Cronbach's alpha was used to measure the internal consistency of the linguistic variables in the regional linguistic data matrix (Nerbonne and Heeringa, 1997;Heeringa et al, 2002;Heeringa, 2004;Nerbonne, 2008;Szmrecsanyi, 2008;Spruit et al, 2009). Cronbach's alpha was originally developed to assess if a set of items in a psychometric test measure the same underlying construct based on the scores on the test items for a sample of test takers (Cronbach, 1951).…”

“…A significant positive correlation indicates that as the geographic distance between locations increases, so does linguistic distance, so that the language of nearby locations tends to be more similar than the language of distant locations. This general approach has also been used to identify regional patterns in the values of individual variables by regressing a geographic distance matrix against a distance matrix based on a single variable (Szmrecsanyi, 2008).…”

“…This method is also sensitive to the density of locations in the dataset. In dialectometry, multidimensional scaling is often used to identify underlying patterns of aggregated regional variation in a linguistic distance matrix Nerbonne and Kleiweg, 2003;Nerbonne, 2010a;Szmrecsanyi, 2008). Multidimensional scaling is a set of statistical methods used for visualizing patterns of proximity between objects in a distance matrix (Cox and Cox, 2001).…”

“…The results of the multidimensional scaling can also be visualized by combining all three dimensions to form a single map using RGB mapping (Nerbonne, 2010a;Szmrecsanyi, 2008). In RGB mapping the three dimensions extracted by the multidimensional scaling are mapped simultaneously by associating each location with a color defined by deriving each of the three RGB color parameters (red, blue and green) from the three dimension scores for that location.…”

Measuring historical word sense variation

“…Researchers in linguistics and the digital humanities have long used large textual corpora to discern variation in language, both for studies in dialectology [42] and stylistics [28,20]. The rise of large digitization projects such as Early English Books Online and of more open transcription efforts such as the EEBO-Text Creation Partnership, however, ushered in collections an order of magnitude larger (to date, EEBO-TCP contains transcriptions of 11,462 documents for a total of 521 million words from 1475-1700), enabling research into the development of English over a period of 300 years [4].…”