Corpus Approaches to Discourse: A Critical Review

Description

Corpus linguistics has now come of age and Corpus Approaches to Discourse equips students with the means to question, defend and refine the methodology. Looking at corpus linguistics in discourse research from a critical perspective, this volume is a call for greater reflexivity in the field. The chapters, each written by leading authorities, contain an overview of an emerging area and a case-study, presenting practical advice alongside theoretical reflection. Carefully structured with an introduction by the editors and a conclusion by leading researcher, Paul Baker, this is key reading for advanced students and researchers of corpus linguistics and discourse analysis. Cover Half Title Title Page Copyright Page Table of Contents List of figures List of tables Contributors Acknowledgements Chapter 1 Introduction: partiality and reflexivity 1.1 Aims 1.2 Qualitative and quantitative 1.3 Triangulation 1.4 Partiality 1.5 Looking forwards Notes References Part A Overlooked areas (checking the dusty corners) Chapter 2 Similarity 2.1 Introduction 2.2 Why is similarity important for corpus and discourse work? 2.3 Similarity and the tools of corpus and discourse research 2.4 Case study: representation of refugees in political and media discourse 2.5 Conclusions Acknowledgements Notes References Chapter 3 Absence: you don’t know what you’re missing. Or do you? 3.1 Introduction: is there something missing from corpus linguistics? 3.2 What is absence? 3.3 What is the impact of overlooking absence/s? 3.4 Approaching absence through corpus-assisted discourse studies 3.5 Case studies 3.6 Evaluations and conclusions Notes References Chapter 4 Overlooked text types: from fictional texts to real-world discourses 4.1 Introduction 4.2 The salient and the overlooked in CADS 4.3 Fiction, fact and meaning 4.4 Literature, style and discourse 4.5 Case study: discourses of gender and sexuality in erotic writing 4.6 Evaluation: fictional stories and their real consequences Notes References Part B Triangulation (identifying blind spots) Chapter 5 Analysing the multimodal text 5.1 Introduction 5.2 Key terms and definitions 5.3 (Corpus) linguistics and ‘new’ media 5.4 The contribution of CAMDA to reducing partiality 5.5 Case study: the Australian federal election and Instagram 5.6 Evaluation Acknowledgements Notes References Chapter 6 Using multiple data sets 6.1 Introduction 6.2 Rationale for using multiple data sets 6.3 Doing CADS with multiple data sets 6.4 Case Study: discursive constructions of postnatal depressions in medical, media and lay contexts 6.5 Evaluation Notes References Chapter 7 Interdisciplinary approaches in corpus linguistics and CADS 7.1 Introduction 7.2 Interdisciplinary approaches in corpus linguistics and C 7.3 Case study: combining corpus linguistics and anthropology 7.4 Discussion and conclusion Notes References Part C Research design (avoiding pitfalls/re-examining the foundations) Chapter 8 The role of the text in corpus and discourse analysis: missing the trees for the forest 8.1 Introduction 8.2 Defining text 8.3 The text in corpus-based discourse analysis 8.4 The text in keyword analysis: a case study 8.5 Conclusion Note References Chapter 9 Dividing up the data: epistemological, methodological and practical impact of diachronic segmentation 9.1 Introduction 9.2 Modern diachronic discourse analysis using corpora 9.3 Segmentation and units 9.4 Case study: the Arab seasons 9.5 Conclusion Notes References Chapter 10 Visualisation in corpus-based discourse studies 10.1 Introduction 10.2 Defining visualisation 10.3 Pitfalls in the traditional presentation of language data 10.4 Research on the principles of effective visualisation 10.5 Language data visualisation: a case study 10.6 Conclusions References Chapter 11 Keyness analysis: nature, metrics and techniques 11.1 Introduction 11.2 Definitions and related issues 11.3 Identifying key items: appropriate metrics 11.4 Selecting key items for analysis 11.5 Selecting key items: a case study 11.6 Conclusion Acknowledgements Notes References Chapter 12 Statistical choices in corpus-based discourse analysis 12.1 Introduction 12.2 Background: statistics meets discourse analysis 12.3 Where to start? Research design and planning 12.4 How to categorise data? Inter-rater agreement 12.5 How to capture meaning relations? Collocations and collocation networks 12.6 How to compare different discourses? T-test and ANOVA 12.7 Conclusion Acknowledgements Note References Chapter 13 Conclusion: reflecting on reflective research 13.1 Introduction 13.2 An impartial approach? 13.3 To be critical? 13.4 Triangulation 13.5 Transparency 13.6 Concluding remarks References Index