Stefan Th. Gries – författare
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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.
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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.
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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 contributions do 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 volume will 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.
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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.
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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.
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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.
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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.
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This book is the revised and extended second edition of Statistics for Linguistics with R. The comprehensive revision includes new small sections on programming topics that facilitate statistical analysis, the addition of a variety of statistical functions readers can apply to their own data, and a revision of overview sections on statistical tests and regression modeling. The main revision is a complete rewrite of the chapter on multifactorial approaches, which now contains sections on linear regression, binary and ordinal logistic regression, multinomial and Poisson regression, and repeated-measures ANOVA.The revisions are completed by a new visual tool to identify the right statistical test for a given problem and data set.
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Ten Lectures on Quantitative Approaches in Cognitive Linguistics
Corpus-linguistic, experimental, and statistical applications
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Ten Lectures on Corpus Linguistics with R
Applications for Usage-Based and Psycholinguistic Research
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