Hands off the metadata!: Comparing the use of explicit and background metadata in crowdsourced dialectology

Abstract

Abstract In this article we assess the extent to which we can collect plausible data about regional dialect variation using crowdsourcing techniques – the BBC Future Survey – without explicitly gathering any user metadata, but relying instead on background information collected by Google Analytics. In order to do this, we compare this approach with another crowdsourced survey, operated from a smartphone application, which examines the same site – the British Isles – but which explicitly asks users to submit detailed social background information – the English Dialects App (EDA) (Leemann et al. 2018). The EDA has the disadvantage that there is a considerable user drop-off between completing the dialect survey and completing the social metadata questionnaire. The BBC Future Survey, however, only collects information on where users are physically located when they complete the survey – not where they are from or even where they live. Results show that the BBC Future Survey produces a plausible snapshot of regional dialect variability that can complement other more sophisticated (expensive, time-consuming) approaches to investigating language variation and change. We suggest the approach constitutes a digital-era rapid anonymous survey along the lines of Labov (1972), serving similar aims, with similar success, but on a much much larger scale.