Triangulating Methodological Approaches in Corpus-Linguistic Research by Paul Baker ISBN 9781317532071, 1317532074 instant download

Triangulating Methodological Approaches in Corpus-Linguistic Research by Paul Baker ISBN 9781317532071, 1317532074 instant download

Contemporary corpus linguists use a wide variety of methods to study discourse patterns. This volume provides a systematic comparison of various methodological approaches in corpus linguistics through a series of parallel empirical studies that use a single corpus dataset to answer the same overarching research question. Ten contributing experts each use a different method to address the same broadly framed research question: In what ways does language use in online Q+A forum responses differ across four world English varieties (India, Philippines, United Kingdom, and United States)? Contributions will be based on analysis of the same 400,000 word corpus from online Q+A forums, and contributors employ methodologies including corpus-based discourse analysis, audience perceptions, Multi-Dimensional analysis, pragmatic analysis, and keyword analysis. In their introductory and concluding chapters, the volume editors compare and contrast the findings from each method and assess the degree to which ‘triangulating’ multiple approaches may provide a more nuanced understanding of a research question, with the aim of identifying a set of complementary approaches which could arguably take into account analytical blind spots. Baker and Egbert also consider the importance of issues such as researcher subjectivity, type of annotation, the limitations and affordances of different corpus tools, the relative strengths of qualitative and quantitative approaches, and the value of considering data or information beyond the corpus. Rather than attempting to find the ‘best’ approach, the focus of the volume is on how different corpus linguistic methodologies may complement one another, and raises suggestions for further methodological studies which use triangulation to enrich corpus-related research.