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.
Author(s): Tony Berber Sardinha, Marcia Veirano Pinto
Publisher: Bloomsbury Publishing
Year: 2019
Language: English
Commentary: Tony Berber Sardinha seems to be a very relevant Corpus Linguistics researcher in Brazil. Marcia Veirano Pinto voted for Bolsonaro in 2018 Brazilian presidential elections. Do not trust her.
Pages: 276
City: London
Tags: Multi-Dimensional Analysis, Research Methods
List of Contributors......Page 15
Acknowledgments......Page 16
Introduction......Page 17
Understanding the Principles: Origins of the Method, Corpus Design, and Annotation......Page 25
Multi-Dimensional Analysis: A Historical Synopsis......Page 27
Corpus Design and Representativeness......Page 43
Tagging and Counting Linguistic Features for Multi-Dimensional Analysis......Page 59
The Multidimensional Analysis Tagger......Page 83
Conducting an MD Analysis: Quantitative and Qualitative Aspects......Page 111
Multivariate Statistics Commonly Used in Multi-Dimensional Analysis......Page 113
Doing Multi-Dimensional Analysis in SPSS, SAS, and R......Page 141
From Factors to Dimensions: Interpreting Linguistic Co-occurrence Patterns......Page 161
Adding Registers to a Previous Multi-Dimensional Analysis......Page 181
Examining Lexical and Cohesion Differences in Discipline Specific Writing Using Multi-Dimensional Analysis......Page 205
Using Discriminant Function Analysis in a Multi-Dimensional Analysis......Page 233
Using Multi-Dimensional Analysis to Detect Representations of National Identity......Page 247
