This volume serves as a comprehensive introduction to Time Series Analysis (TSA), used commonly in financial and engineering sciences, to demonstrate its potential to complement qualitative approaches in discourse analysis research. The book begins by discussing how time has previously been conceptualized in the literature, drawing on studies from variationist sociolinguistics, corpus linguistics, and Critical Discourse Analysis. The volume then segues into a discussion of how TSA is applied in other contexts in which observed values are expected to be dependent on earlier values, such as stock markets and sales figures, and introduces a range of discourse-specific contexts to show how the technique might be extended to analyze trends or shed further light on relevant themes in discourse over time. Each successive chapter features a different discourse context as a case study, from psychotherapy sessions, university lectures, and news articles, and looks at how studying different variables over time in each context – metaphors, involvement markers, and keywords, respectively – can contribute to a greater understanding of both present and future discourse activity in these settings. Taken together, this book highlights the value of TSA as a complementary approach to meaning-based analysis in discourse, making this ideal reading for graduate students and scholars in discourse analysis looking to employ quantitative methods in their research practice.
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Dennis Tay is an Associate Professor at the Department of English, The Hong Kong Polytechnic University. His research interests include cognitive linguistics, discourse analysis, mental healthcare communication, and the statistical modeling of discourse.
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Dennis Tay is an Associate Professor at the Department of English, The Hong Kong Polytechnic University. His research interests include cognitive linguistics, discourse analysis, mental healthcare communication, and the statistical model. Nº de ref. del artículo: 594600045
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