Multi-dimensional analysis : research methods and current issues
著者
書誌事項
Multi-dimensional analysis : research methods and current issues
Bloomsbury Academic, 2021
- : pbk
大学図書館所蔵 全3件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
"First published in Great Britain 2019. Paperback edition published 2021"-- T.p.verso
Includes bibliographical references and index
内容説明・目次
内容説明
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.
目次
Preface
Introduction, Tony Berber Sardinha and Marcia Veirano Pinto (Sao 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, Bethany 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, Tony Berber Sardinha, Marcia Veirano Pinto, Carlos Kauffmann, Carolina Zuppardi and Cristina Mayer Acunzo (Sao Paulo Catholic University, Brazil)
Part III. Exploring the method
9. Examining lexical and cohesion differences in discipline specific writing using MDA, Scott A. Crossley, Kristopher Kyle and Ute Roemer (Georgia State University, USA)
10. Using Discriminate Function Analysis in multi-dimensional analysis, Marcia Veirano Pinto (Sao Paulo Catholic University, Brazil)
11. Using multidimensional analysis to detect representations of national identity, Tony Berber Sardinha (Sao Paulo Catholic University, Brazil)
Bibliography
Index
「Nielsen BookData」 より