Data Analytics for Discourse Analysis with Python

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.