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Studies based on the Corpus of Early English Correspondence
What role has social status played in shaping the English language across the centuries? Have women also been the agents of language standardization in the past? Can apparent-time patterns be used to predict the course of long-term language change?
These questions and many others will be addressed in this volume, which combines sociolinguistic methodology and social history to account for diachronic language change in Renaissance English. The approach has been made possible by the new machine-readable Corpus of Early English Correspondence (CEEC) specifically compiled for this purpose. The 2.4-million-word corpus covers the period from 1420 to 1680 and contains over 700 writers.
The volume introduces the premises of the study, discussing both modern sociolinguistics and English society in the late medieval and early modern periods. A detailed description is given of the Corpus of Early English Correspondence, its encoding, and the separate database which records the letter writers' social backgrounds.
The pilot studies based on the CEEC suggest that social rank and gender should both be considered in diachronic language change, but that apparent-time patterns may not always be a reliable cue to what will happen in the long run. The volume also argues that historical sociolinguistics offers fascinating perspectives on the study of such new areas as pragmatization and changing politeness cultures across time.
This extension of sociolinguistic methodology to the past is a breakthrough in the field of corpus linguistics. It will be of major interest not only to historical linguists but to modern sociolinguists and social historians.

Abstract

This introductory chapter begins by considering how the fields of corpus linguistics, digital linguistics and digital humanities overlap, intertwine and feed off each other when it comes to making use of the increasing variety of resources available for linguistic research today. We then move on to discuss the benefits and challenges of three partly overlapping approaches to the use of digital data sources: (1) increasing data size to create “big data”, (2) supplying multi-faceted co(n)textual information and analyses to produce “rich data”, and (3) adapting existing data sets to new uses by drawing on hitherto “uncharted data”. All of them also call for new digital tools and methodologies that, in Tim Hitchcock’s words, “allow us to think small; at the same time as we are generating tools to imagine big.” We conclude the chapter by briefly describing how the contributions in this volume make use of their various data sources to answer new research questions about language use and to revisit old questions in new ways.

In: From Data to Evidence in English Language Research
In: From Data to Evidence in English Language Research
In: From Data to Evidence in English Language Research
In: From Data to Evidence in English Language Research