Multi-Dimensional Analysis: Research Methods and Current Issues

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.

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.