The first textbook of its kind, Quantitative Corpus Linguistics with R demonstrates how to use the open source programming language R for corpus linguistic analyses. Computational and corpus linguists doing corpus work will find that R provides an enormous range of functions that currently require several programs to achieve – searching and processing corpora, arranging and outputting the results of corpus searches, statistical evaluation, and graphing.
An investigation into the way people use language in speech and writing, this volume introduces the corpus-based approach, which is based on analysis of large databases of real language examples stored on computer.
This handbook is a comprehensive practical resource on corpus linguistics. It features a range of basic and advanced approaches, methods and techniques in corpus linguistics, from corpus compilation principles to quantitative data analyses. The Handbook is organized in six Parts. Parts I to III feature chapters that discuss key issues and the know-how related to various topics around corpus design, methods and corpus types. Parts IV-V aim to offer a user-friendly introduction to the quantitative analysis of corpus data: for each statistical technique discussed, chapters provide a practical guide with R and come with supplementary online material. Part VI focuses on how to write a corpus linguistic paper and how to meta-analyze corpus linguistic research. The volume can serve as a course book as well as for individual study. It will be an essential reading for students of corpus linguistics as well as experienced researchers who want to expand their knowledge of the field.
Specialised linguistic research needs can no longer be met by available software. This book enables the researcher to write programs for text and corpus processing, using the popular and easy to learn Java language.
This Element offers intermediate or experienced programmers algorithms for Corpus Linguistic (CL) programming in the Python language using dataframes that provide a fast, efficient, intuitive set of methods for working with large, complex datasets such as corpora. This Element demonstrates principles of dataframe programming applied to CL analyses, as well as complete algorithms for creating concordances; producing lists of collocates, keywords, and lexical bundles; and performing key feature analysis. An additional algorithm for creating dataframe corpora is presented including methods for tokenizing, part-of-speech tagging, and lemmatizing using spaCy. This Element provides a set of core skills that can be applied to a range of CL research questions, as well as to original analyses not possible with existing corpus software.
Corpus analysis can be expanded and scaled up by incorporating computational methods from natural language processing. This Element shows how text classification and text similarity models can extend our ability to undertake corpus linguistics across very large corpora. These computational methods are becoming increasingly important as corpora grow too large for more traditional types of linguistic analysis. We draw on five case studies to show how and why to use computational methods, ranging from usage-based grammar to authorship analysis to using social media for corpus-based sociolinguistics. Each section is accompanied by an interactive code notebook that shows how to implement the analysis in Python. A stand-alone Python package is also available to help readers use these methods with their own data. Because large-scale analysis introduces new ethical problems, this Element pairs each new methodology with a discussion of potential ethical implications.
This is the first book of its kind to provide a practical and student-friendly guide to corpus linguistics that explains the nature of electronic data and how it can be collected and analyzed. Designed to equip readers with the technical skills necessary to analyze and interpret language data, both written and (orthographically) transcribed Introduces a number of easy-to-use, yet powerful, free analysis resources consisting of standalone programs and web interfaces for use with Windows, Mac OS X, and Linux Each section includes practical exercises, a list of sources and further reading, and illustrated step-by-step introductions to analysis tools Requires only a basic knowledge of computer concepts in order to develop the specific linguistic analysis skills required for understanding/analyzing corpus data
This textbook examines empirical linguistics from a theoretical linguist’s perspective. It provides both a theoretical discussion of what quantitative corpus linguistics entails and detailed, hands-on, step-by-step instructions to implement the techniques in the field. The statistical methodology and R-based coding from this book teach readers the basic and then more advanced skills to work with large data sets in their linguistics research and studies. Massive data sets are now more than ever the basis for work that ranges from usage-based linguistics to the far reaches of applied linguistics. This book presents much of the methodology in a corpus-based approach. However, the corpus-based methods in this book are also essential components of recent developments in sociolinguistics, historical linguistics, computational linguistics, and psycholinguistics. Material from the book will also be appealing to researchers in digital humanities and the many non-linguistic fields that use textual data analysis and text-based sensorimetrics. Chapters cover topics including corpus processing, frequencing data, and clustering methods. Case studies illustrate each chapter with accompanying data sets, R code, and exercises for use by readers. This book may be used in advanced undergraduate courses, graduate courses, and self-study.
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.
The use of large, computerized bodies of text for linguistic analysis and description has emerged in recent years as one of the most significant and rapidly-developing fields of activity in the study of language. This book provides a comprehensive introduction and guide to Corpus Linguistics. All aspects of the field are explored, from the various types of electronic corpora that are available to instructions on how to design and compile a corpus. Graeme Kennedy surveys the development of corpora for use in linguistic research, looking back to the pre-electronic age as well as to the massive growth of computer corpora in the electronic age.
