Multi-Dimensional Analysis

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. It looks at register, corpus building, tagging and tools. It shows how such elements are explored in latest research findings, which have pushed the limits of MDA by applying it to specialized registers as well as lexical cohesion.

Multi-dimensional analysis is a method that allows the researcher to describe different registers (textual varieties defined by their social use) by identifying complementary correlation groupings of dozens of variables through factor analysis. This includes 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 formality to determine linguistic constructs known as dimensions of variation, which provide a scale for the comparison of a large number of texts and registers. The first research on the method was first published in 1988 by Douglas Biber, however, due to difficulties related both to the tagging and counting of such an array of linguistic features and to access to statistical software packages in the past decades, it has only become popular in recent years, with more and more researchers availing themselves of this powerful method to describe variation in a diversity of linguistic domains such as academic settings, regional discourse, social media, movies and pop songs.

This book is a complete research guide to MDA.