In this book, Stefan Th. Gries provides an overview on how quantitative corpus methods can provide insights to cognitive/usage-based linguistics and selected psycholinguistic questions. Topics include the corpus linguistics in general, its most important methodological tools, its statistical nature, and the relation of all these topics to past and current usage-based theorizing. Central notions discussed in detail include frequency, dispersion, context, and others in a variety of applications and case studies; four practice sessions offer short introductions of how to compute various corpus statistics with the open source programming language and environment R.

This series of lectures provides an overview of the author's work on quantitative applications in cognitive linguistics by discussing a wide range of studies involving corpus-linguistic as well as experimental work. After a discussion of how corpus linguistics, cognitive linguistics, and psycholinguistics relate to each other, the author discusses empirical and statistical studies of a wide variety of phenomena including morphophonology (morphological blends and alliteration effects), corpus-based cognitive semantics, frequency and association at the syntax-lexis interface. The book concludes with chapters exemplifying the role that bottom-up approaches can take, the role of statistical methods more generally, and the role of converging evidence from corpus and experimental data.The lectures for this book were given at The China International Forum on Cognitive Linguistics in May 2013. In the e-book version all handouts have been made available at the back. All audio of the lectures as well as the handouts are available for free, in Open Access, here.

The volume explores the relationship between well-studied aspects of language (constructional alternations, lexical contrasts and extensions and multi-word expressions) in a variety of languages (Dutch, English, Russian and Spanish) and their representation in cognition as mediated by frequency counts in both text and experiment. The state-of-the-art data collection (ranging from questionnaires to eye-tracking) and analysis (from simple chi-squared to random effects regression) techniques allow to draw theoretical conclusions from (mis)matches between different types of empirical data. The sister volume focuses on language learning and processing.

The volume contains a collection of studies on how the analysis of corpus and psycholinguistic data reveal how linguistic knowledge is affected by the frequency of linguistic elements/stimuli. The studies explore a wide range of phenomena, from phonological reduction processes and palatalization to morphological productivity, diachronic change, adjective preposition constructions, auxiliary omission, and multi-word units. The languages studied are Spanish and artificial languages, Russian, Dutch, and English. The sister volume focuses on language representation.

This book is an introduction to statistics for linguists using the open source software R. It is aimed at students and instructors/professors with little or no statistical background and is written in a non-technical and reader-friendly/accessible style. It first introduces in detail the overall logic underlying quantitative studies: exploration, hypothesis formulation and operationalization, and the notion and meaning of significance tests. It then introduces some basics of the software R relevant to statistical data analysis. A chapter on descriptive statistics explains how summary statistics for frequencies, averages, and correlations are generated with R and how they are graphically represented best. A chapter on analytical statistics explains how statistical tests are performed in R on the basis of many different linguistic case studies: For nearly every single example, it is explained what the structure of the test looks like, how hypotheses are formulated, explored, and tested for statistical significance, how the results are graphically represented, and how one would summarize them in a paper/article. A chapter on selected multifactorial methods introduces how more complex research designs can be studied: methods for the study of multifactorial frequency data, correlations, tests for means, and binary response data are discussed and exemplified step-by-step. Also, the exploratory approach of hierarchical cluster analysis is illustrated in detail. The book comes with many exercises, boxes with short think breaks and warnings, recommendations for further study, and answer keys as well as a statistics for linguists newsgroup on the companion website. The volume is aimed at beginners on every level of linguistic education: undergraduate students, graduate students, and instructors/professors and can be used in any research methods and statistics class for linguists. It presupposes no quantitative/statistical knowledge whatsoever and, unlike most competing books, begins at step 1 for every method and explains everything explicitly.

As in its first edition, the new edition of Quantitative Corpus Linguistics with R demonstrates how to process corpus-linguistic data with the open-source programming language and environment R. Geared in general towards linguists working with observational data, and particularly corpus linguists, it introduces R programming with emphasis on: data processing and manipulation in general; text processing with and without regular expressions of large bodies of textual and/or literary data, and; basic aspects of statistical analysis and visualization. This book is extremely hands-on and leads the reader through dozens of small applications as well as larger case studies. Along with an array of exercise boxes and separate answer keys, the text features a didactic sequential approach in case studies by way of subsections that zoom in to every programming problem. The companion website to the book contains all relevant R code (amounting to approximately 7,000 lines of heavily commented code), most of the data sets as well as pointers to others, and a dedicated Google newsgroup. This new edition is ideal for both researchers in corpus linguistics and instructors who want to promote hands-on approaches to data in corpus linguistics courses.

As in its first edition, the new edition of Quantitative Corpus Linguistics with R demonstrates how to process corpus-linguistic data with the open-source programming language and environment R. Geared in general towards linguists working with observational data, and particularly corpus linguists, it introduces R programming with emphasis on: data processing and manipulation in general; text processing with and without regular expressions of large bodies of textual and/or literary data, and; basic aspects of statistical analysis and visualization. This book is extremely hands-on and leads the reader through dozens of small applications as well as larger case studies. Along with an array of exercise boxes and separate answer keys, the text features a didactic sequential approach in case studies by way of subsections that zoom in to every programming problem. The companion website to the book contains all relevant R code (amounting to approximately 7,000 lines of heavily commented code), most of the data sets as well as pointers to others, and a dedicated Google newsgroup. This new edition is ideal for both researchers in corpus linguistics and instructors who want to promote hands-on approaches to data in corpus linguistics courses.

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.

This is the third, newly revised and extended edition of this successful book (that has already been translated into three languages). Like the previous editions, it is entirely based on the programming language and environment R and is still thoroughly hands-on (with thousands of lines of heavily annotated code for all computations and plots). However, this edition has been updated based on many workshops/bootcamps taught by the author all over the world for the past few years: This edition has been didactically streamlined with regard to its exposition, it adds two new chapters - one on mixed-effects modeling, one on classification and regression trees as well as random forests - plus it features new discussion of curvature, orthogonal and other contrasts, interactions, collinearity, the effects and emmeans packages, autocorrelation/runs, some more bits on programming, writing statistical functions, and simulations, and many practical tips based on 10 years of teaching with these materials.

The papers in this volume deal with the issue of how corpus data relate to the questions that cognitive linguists have typically investigated with respect to conceptual mappings. The authors in this volume investigate a wide range of issues- the coherence and function of particular metaphorical models, the interaction of form and meaning, the identification of source domains of metaphorical expressions, the relationship between metaphor and discourse, the priming of metaphors, and the historical development of metaphors. The studies deal with a variety of metaphorical and metonymic source and target domains, including the source domains SPACE, ANIMALS, BODY PARTS, ORGANIZATIONS and WAR, and the target domains VERBAL ACTIVITY, ECONOMY, EMOTIONS and POLITICS. In their studies, the authors present a variety of corpus-linguistic methods for the investigation of conceptual mappings, for example, corpora annotated for semantic categories, concordances of individual source-domain items and patterns, and concordances of target-domain items. In sum, the papers in this volume show how a wide range of corpus-linguistic methods can be used to investigate a variety of issues in cognitive linguistics; the combination of corpus methods with a cognitive-linguistic view of metaphor and metonymy yields new answers to old questions (and to new questions) about the relationship between language as a conceptual phenomenon and language as a textual phenomenon.

Cognitive Linguistics, the branch of linguistics that tries to "make one's account of human language accord with what is generally known about the mind and the brain," has become one of the most flourishing fields of contemporary linguistics. The chapters address many classic topics of Cognitive Linguistics. These topics include studies on the semantics of specific words (including polysemy and synonymy) as well as semantic characteristics of particular syntactic patterns / constructions (including constructional synonymy and the schematicity of constructions), the analysis of causatives, transitivity, and image-schematic aspects of posture verbs. The key characteristic of this volume is that all papers adopt the methodological perspective of Corpus Linguistics, the rapidly evolving branch of linguistics based on the computerized analysis of language used in authentic settings. Thus, the contributionsdo not only all provide various new insights in their respective fields, they also introduce new data as well as new corpus-based and quantitative methods of analysis. On the basis of their findings, the authors discuss both theoretical implications going well beyond the singular topics of the studies and show how the discipline of Cognitive Linguistics can benefit from the rigorous analysis of naturally-occurring language. The languages which are investigated are English, German, Dutch, and Russian, and the data come from a variety of different corpora. As such, the present volumewill be of interest to a wide range of scholars with many different foci and interests and should pave the way for further integration of usage-based techniques of analysis within this exciting paradigm.