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.

This concise volume, using examples of psychotherapy talk, showcases the potential applications of data analytics for advancing discourse research and other related disciplines. The book provides a brief primer on data analytics, defined as the science of analyzing raw data to reveal new insights and support decision making. Currently underutilized in discourse research, Tay draws on the case of psychotherapy talk, in which clients’ concerns are worked through via verbal interaction with therapists, to demonstrate how data analytics can address both practical and theoretical concerns. Each chapter follows a consistent structure, offering a streamlined walkthrough of a key technique, an example case study, and annotated Python code. The volume shows how techniques such as simulations, classification, clustering, and time series analysis can address such issues as incomplete data transcripts, therapist–client (a)synchrony, and client prognosis, offering inspiration for research, training, and practitioner self-reflection in psychotherapy and other discourse contexts. This volume is a valuable resource for discourse and linguistics researchers, particularly for those interested in complementary approaches to qualitative methods, as well as active practitioners.

"Time series analysis is applicable in a variety of disciplines such as business administration, economics, public finances, engineering, statistics, econometrics, mathematics and actuarial sciences. Forecasting the future assists in critical organizationa"

Temporal and spatiotemporal data form an inherent fabric of the society as we are faced with streams of data coming from numerous sensors, data feeds, recordings associated with numerous areas of application embracing physical and human-generated phenomena (environmental data, financial markets, Internet activities, etc.). A quest for a thorough analysis, interpretation, modeling and prediction of time series comes with an ongoing challenge for developing models that are both accurate and user-friendly (interpretable). The volume is aimed to exploit the conceptual and algorithmic framework of Computational Intelligence (CI) to form a cohesive and comprehensive environment for building models of time series. The contributions covered in the volume are fully reflective of the wealth of the CI technologies by bringing together ideas, algorithms, and numeric studies, which convincingly demonstrate their relevance, maturity and visible usefulness. It reflects upon the truly remarkable diversity of methodological and algorithmic approaches and case studies. This volume is aimed at a broad audience of researchers and practitioners engaged in various branches of operations research, management, social sciences, engineering, and economics. Owing to the nature of the material being covered and a way it has been arranged, it establishes a comprehensive and timely picture of the ongoing pursuits in the area and fosters further developments.

The overarching theme of Discourse and Technology is cutting-edge in the field of linguistics: multimodal discourse. This volume opens up a discussion among discourse analysts and others in linguistics and related fields about the two-fold impact of new communication technologies: The impact on how discourse data is collected, transcribed, and analyzed—and the impact that these technologies are having on social interaction and discourse. As inexpensive tape recorders allowed the field to move beyond text, written or printed language, to capture talk—discourse as spoken language—the information explosion (including cell phones, video recorders, Internet chat rooms, online journals, and the like) has moved those in the field to recognize that all discourse is, in various ways, "multimodal," constructed through speech and gesture, as well as through typography, layout, and the materials employed in the making of texts. The contributors have responded to the expanding scope of discourse analysis by asking five key questions: Why should we study discourse and technology and multimodal discourse analysis? What is the role of the World Wide Web in discourse analysis? How does one analyze multimodal discourse in studies of social actions and interactions? How does one analyze multimodal discourse in educational social interactions? and, How does one use multimodal discourse analyses in the workplace? The vitality of these explorations opens windows onto even newer horizons of discourse and discourse analysis.