This volume introduces a new framework for conceptualizing and achieving corpus representativeness in a rigorous, yet practical way.

A linguistic corpus is a collection of texts which have been selected and brought together so that language can be studied on the computer. Today, corpus linguistics offers some of the most powerful new procedures for the analysis of language, and the impact of this dynamic and expanding sub-discipline is making itself felt in many areas of language study. In this volume, a selection of leading experts in various key areas of corpus construction offer advice in a readable and largely non-technical style to help the reader to ensure that their corpus is well designed and fit for the intended purpose. This guide is aimed at those who are at some stage of building a linguistic corpus. Little or no knowledge of corpus linguistics or computational procedures is assumed, although it is hoped that more advanced users will find the guidelines here useful. It is also aimed at those who are not building a corpus, but who need to know something about the issues involved in the design of corpora in order to choose between available resources and to help draw conclusions from their studies.

Paradoxically, doing corpus linguistics is both easier and harder than it has ever been before. On the one hand, it is easier because we have access to more existing corpora, more corpus analysis software tools, and more statistical methods than ever before. On the other hand, reliance on these existing corpora and corpus linguistic methods can potentially create layers of distance between the researcher and the language in a corpus, making it a challenge to do linguistics with a corpus. The goal of this Element is to explore ways for us to improve how we approach linguistic research questions with quantitative corpus data. We introduce and illustrate the major steps in the research process, including how to: select and evaluate corpora, establish linguistically-motivated research questions, observational units and variables, select linguistically interpretable variables, understand and evaluate existing corpus software tools, adopt minimally sufficient statistical methods, and qualitatively interpret quantitative findings.

Corpora are well-established as a resource for language research; they are now also increasingly being used for teaching purposes. This book is the first of its kind to deal explicitly and in a wide-ranging way with the use of corpora in teaching. It contains an extensive collection of articles by corpus linguists and practising teachers, covering not only the use of data to inform and create teaching materials but also the direct exploitation of corpora by students, both in the study of linguistics in general and in the acquisition of proficiency in individual languages, including English, Welsh, German, French and Italian. In addition, the book offers practical information on the sources of corpora and concordances, including those suitable for work on non-roman scripts such as Greek and Cyrillic.

Analysing Representation: A Corpus and Discourse Textbook guides readers through the process of researching how people and phenomena are represented in discourse and introduces them to key tools they can use from corpus linguistics and (critical) discourse analysis. This book takes a step-by-step approach to introducing each concept and includes exercises and further reading to help readers check their progress and prepare for independent research. It is unique in introducing readers to a range of experts representing the full range of work in this area. This book is aimed at final-year undergraduate, taught postgraduate and doctoral level students. It wil also be useful to scholars who are new to combining corpus and discourse methods in investigations of representation.

Multi-Dimensional Analysis: Research Methods and Current Issues provides a comprehensive guide both to the statistical methods in Multi-Dimensional Analysis (MDA) and its key elements, such as corpus building, tagging, and tools. The major goal is to explain the steps involved in the method so that readers may better understand this complex research framework and conduct MD research on their own. Multi-Dimensional Analysis is a method that allows the researcher to describe different registers (textual varieties defined by their social use) such as academic settings, regional discourse, social media, movies, and pop songs. Through multivariate statistical techniques, MDA identifies complementary correlation groupings of dozens of variables, including variables which belong both to the grammatical and semantic domains. Such groupings are then associated with situational variables of texts like information density, orality, and narrativity to determine linguistic constructs known as dimensions of variation, which provide a scale for the comparison of a large number of texts and registers. This book is a comprehensive research guide to MDA.

Gives a theoretical and empirical grounding for quantitative corpus linguistic research in first and second language writing development.