Multi-Dimensional Analysis, 25 years on

Name: Multi-Dimensional Analysis, 25 years on | A tribute to Douglas Biber
Brand: John Benjamins Publishing Company
Price: 118.99 EUR
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A tribute to Douglas Biber

Tony Berber Sardinha Marcia Veirano Pinto(Herausgeber*in)

John Benjamins Publishing Company

1. Auflage

Erschienen am 31. Juli 2014

XXXVIII, 328 Seiten

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Multi-Dimensional Analysis, 25 years on
Editorial page
Title page
LCC data
Dedication page
Table of contents
List of contributors
Preface
Acknowledgments
Introduction
References
Opening
Multi-Dimensional Analysis
References
Part 1. Multi-Dimensional analysis and synchronic analyses
A Multi-Dimensional analysis of regional variation in American English
1. Introduction
2. Corpus
3. Variable selection
4. Local spatial autocorrelation analysis
5. Factor analysis
5.1 Factor 1
5.2 Factor 2
5.3 Factor 3
6. Discussion
References
Appendix
Dimensions of register variation in Brazilian Portuguese
1. Introduction
2. Methods
3. Interpretation of the factors
4. Discussion and conclusion
Acknowledgments
References
Appendix
25 years later: Comparing Internet and pre-Internet registers
1. Introduction
2. Goals, methods, and research questions
3. Adding the Internet registers to the pre-Internet register dimensions
3.1 Dimension 1
3.2 Dimension 2
3.3 Dimension 3
3.4 Dimension 4
3.5 Dimension 5
4. Comparing Internet and pre-Internet registers
5. Conclusions
Acknowledgments
References
Appendix
Part 2. Multi-Dimensional analysisand diachronic analyses
Dimensions of variation in North American movies
1. Introduction
2. Method and corpus
2.1 The North American Movie Corpus (NAMC)
2.2 Situational variables
2.3 MD analysis: An overview
3. Findings
3.1 Dimension 1: Focus on the expression of stance vs. focus on the expression of information
3.2 Dimension 2: Spontaneous vs. non-spontaneous discourse
3.3 Dimension 3: Focus on the expression arguments vs. focus on the reporting of events
3.4 Dimension 4: Focus on attitudinal discourse
3.5 Dimension 5: Situational vs. interpersonal focus
3.6 Dimension 6: Focus on the expression of persuasion
3.7 Dimension 7: Focus on the overt expression of characters' nature
4. Conclusion
Acknowledgements
References
Appendix 1
App endix 2
Dimension scores
Multi-Dimensional analysis of pop songs
1. Introduction
2. Goals and method
3. Dimensions of variation in pop songs
3.1 Lexico-grammatical dimensions
3.1.1 Lexico-grammatical dimension 1: Persuasion
3.1.2 Lexico-grammatical dimension 2: Interaction
3.1.3 Lexico-grammatical dimension 3: Narrative concerns
3.2 Semantic dimensions
3.2.1 Semantic dimension 1: Personal action
3.2.2 Semantic dimension 2: Emotion and society
3.2.3 Semantic dimension 3: Musical reference
4. Conclusion
Acknowledgments
References
Appendix 2
Dimensions of variation in TIME magazine
1. Introduction
2. Method
3. Adding TIME to the 1988 dimensions
4. TIME magazine's own dimensions
5. Variation associated with external circumstances
6. Text types
7. Summary and conclusion
Acknowledgments
References
Part 3. Multi-Dimensional Analysis and language learning
A Multi-Dimensional analysis of essay writing
1. Introduction
1.1 Essay writing
1.2 Writing development
1.3 Essay quality
2. Method
Anchor 156
2.2 Parameters
2.2.1 Essay scoring
2.2.2 Prompt
2.2.3 Grade level
2.2.4 Geographic area
2.2.5 Production type
2.2.6 Timing
Anchor 164
2.3.1 Basic text properties
2.3.2 Basic lexical types
2.3.3 Lexical overlap
2.3.4 Semantic overlap
2.3.5 Givenness
2.3.6 Causality
2.3.7 Connectives
Anchor 172
2.3.9 Anaphoric reference
2.3.10 Spatial cohesion
2.3.11 Temporal cohesion
2.3.12 Contextual cohesion indices
2.3.13 Rhetorical indices
2.3.14 Syntactic complexity
2.3.15 Syntactic similarity
Anchor 180
2.3.17 Syntactic categories
2.3.18 Readability formulas
2.3.19 Easability scores
2.3.20 Minimal edit distance
2.3.21 Word frequency
2.3.22 N-gram indices
2.3.23 N-gram accuracy
Anchor 188
2.3.25 N-gram proportion
2.3.26 Lexical diversity
2.3.27 Word property indices
2.3.28 Hypernymy
2.3.29 Polysemy
2.4 Statistical analysis
3. Results
Anchor 196
3.2 Dimension analysis
3.2.1 Dimension 1 (Essay Quality: Interval Scale)
3.2.2 Dimension 2 (Essay Quality: Low, Middle, High)
3.2.3 Dimension 3 (Prompt and Assignment)
3.2.4 Dimension 4 (Low vs. High Grade Level)
4. Discussion
4.1 Essay quality
Anchor 204
4.3 Grade level
5. Conclusion
Acknowledgments
References
Appendix 1
Appendix 2
A Multi-Dimensional analysis of advanced written L2 Spanish
1. Introduction
1.1 Multi-Dimensional analysis and English academic writing
1.2 Multi-Dimensional analysis and Spanish academic writing
2. Methodology
2.1 Corpus description
2.2 Procedures: Tagging, searching, and norming
2.3 actor analysis
3. Results
3.1 Dimension 1: Expository prose
3.2 Dimension 2: Reporting past events
3.3 Dimension 3: Defining/explaining
3.4 Dimension 4: Hypothesizing about instructional practices
3.5 Dimension 5: Speculating about past actions
3.6 Dimension 6: Expressing causal relations in instructional settings (causal focus)
4. Discussion and conclusions
References
Appendix
Part 4. Multi-Dimensional Analysis: Exploring the methodology
Expanding Multi-Dimensional Analysis with qualitative research techniques
1. Introduction
2. The study
2.1 Background: Why study civil engineering?
2.2 The corpus
2.3 Analysis: Applying Biber's (1988) dimensions of variation in English
2.4 The use of interviews
3. Findings: The MD analysis
3.1 Dimension 3: Elaborated vs. Situation-Dependent reference
3.2 Dimension 5: Abstract vs. non-abstract style
3.3 Problems with student writing: The MD analysis perspective
4. Findings: The interviews' contribution
4.1 Students: 'It looks better if it's longer.'
4.2 Students: 'The tech writing thing of no I, no we, no you.'
4.3 Practitioners: 'Unambiguous writing is one way to prevent unintentional liability.'
5. Conclusion: Integrating MD analysis and qualitative techniques
Acknowledgements
References
Appendix
MD Scores for Civil Engineering Registers
Conducting Multi-Dimensional analysis using SPSS
1. Introduction
2. A step-by-step guide
2.1 SPSS v.18 and SPSS tutorials
3. Obtaining a dataset for FA
3.1 Sample size and multivariate assumptions
3.2 Overview of FA steps in SPSS
4. Running FA
4.1 SPSS commands to produce the FA dialog box
4.2 Interpreting your output
3.3 Rotation
5. Interpreting factors (from factors to dimensions)
5.1 Computing dimension scores
6. Summary
References
Appendix
Author index
Subject index

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