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Zusatztext This book is a must-read for anyone who wishes to carry out multi-dimensional analyses of corpora. It consists of a collection of chapters written by experts in the field which take the reader through the origins of the approach and along its different methodological stages, drawing on a range of examples as well as offering a detailed account of existing MD research. It encourages, enlightens and enables future MD analysts. Informationen zum Autor Tony Berber Sardinha is a professor with the Applied Linguistics Graduate Program and the Linguistics Dept, São Paulo Catholic University, Brazil. He has published numerous books and research articles, and is on the board of several journals and book collections. His interests are corpus linguistics, metaphor analysis, and applied linguistics. Marcia Veirano Pinto is a Professor in the School of Philosophy, Languages and Humanities, São Paulo Federal University, Brazil and is a member of the editorial body of the journal DELTA: Documentação e estudos em linguística teórica e aplicada . She is a co-editor of books on corpus linguistics and has authored several book chapters on EFL and corpus research. Vorwort A comprehensive guide to multi-dimensional analysis, looking at its foundational history, statistical methods and its key elements. The book examines register, corpus building, tagging and tools. Zusammenfassung 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. Inhaltsverzeichnis PrefaceIntroduction, Tony Berber Sardinha and Marcia Veirano Pinto (São Paulo Catholic University, Brazil) Part I: Understanding the principles: origins of the method, corpus design and annotation 1. Multi-dimensional analysis: a historical synopsis, Douglas Biber (Northern Arizona University, USA) 2. Corpus design and representativeness, Jesse Egbert (Brigham Young University, USA) 3. Tagging and counting linguistic features for multi-dimensional analysis, B ethany Gray (Iowa State University, USA) 4. The Multi-dimensional Analysis Tagger, Andrea Nini (Aston University, UK) Part II: Conducting an MD analysis: Quantitative and qualitative analysis 5. Multivariate statistics commonly used in multi-dimensional analysis, Pascual Cantos Gomez (University of Murcia, Spain) 6. Doing multi-dimensional analysis in SPSS, SAS and R, Jesse Egbert (Northern Arizona University, USA) and Shelley Staples (Purdue University, USA) 7. From factors to dimensions: interpreting linguistic co-ocurrence patterns, Eric Friginal (Georgia State University, USA) and Jack Hardy (Emory College of Arts and Science, USA) 8. Adding registers to a previous multi-dimensional analysis, T ony Berber Sardinha, Marcia Veirano Pinto, Carlos Kauffmann, Carolina Zuppardi and ...
