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This chapter provides an overview of computational work in dialectology. This chapter is written for computational linguists, so that we will focus less on the technical details of exploiting the computer in research on dialects (which is documented in the articles we cite) but rather more on background assumptions and emerging issues and opportunities.

An important objective of research in Second Language Acquisition has been to find a simple and reliable way to quantify second language use. Corpora have provided a crucial source of information for these studies. In spite of many attempts to determine an optimal “yardstick” to measure the quality of second language use, particularly lexical complexity and syntactic complexity, a reliable and widely applicable instrument has not yet been determined. The difficulty in finding a suitable instrument can be accounted for in a complex dynamic systems theory (CDST) approach to second language development. An important starting point of this approach is that every next step in time “is the emergent product of context and history, and no component has causal priority” (Thelen 2005, p. 271). In this paper we illustrate this by using a dense longitudinal corpus of the development of 22 highly similar L2 learners, consisting of 23 weekly measurements. The analysis of these data show convincingly that L2 development is a highly individually owned and nonlinear process. While complexity yardsticks (like MLTU and Guiraud) may seem functional from a group perspective, their application to individual learners is very limited.

This paper provides an overview of computational work in dialectology. We have published similar surveys in the not-too-distant past (Heeringa and Prokic, 2018; Wieling and Nerbonne, 2015), but these were aimed at dialectologists and general linguists, respectively. This article is aimed at computational linguists, so that we will focus less on the nuts and bolts of exploiting the computer in research on dialects (which is documented in the articles we cite) and more on background assumptions and emerging issues and opportunities.

An important objective of research in Second Language Acquisition has been to find a simple and reliable way to quantify second language use. Corpora have provided a crucial source of information for these studies. In spite of many attempts to determine an optimal “yardstick” to measure the quality of second language use, particularly lexical complexity and syntactic complexity, a reliable and widely applicable instrument has not yet been determined. The difficulty in finding a suitable instrument can be accounted for in a complex dynamic systems theory (CDST) approach to second language development. An important starting point of this approach is that every next step in time “is the emergent product of context and history, and no component has causal priority” (Thelen 2005, p. 271). In this paper we illustrate this by using a dense longitudinal corpus of the development of 22 highly similar L2 learners, consisting of 23 weekly measurements. The analysis of these data show convincingly that L2 development is a highly individually owned and nonlinear process. While complexity yardsticks (like MLTU and Guiraud) may seem functional from a group perspective, their application to individual learners is very limited.