This article presents a novel framework for examining how emotional labor is performed linguistically. Bringing together Arlie Hochschild's pioneering sociological work and insights from the linguistic literature on emotion, the framework aims to capture the discursive mechanisms through which workers express, background and manage emotions in fulfilling their professional roles. We demonstrate the framework through a case study of a corpus of Twitter interactions involving passengers and airline customer service agents during the first wave of the Covid-19 pandemic. Following recent calls for triangulation in corpus linguistics, we explore the corpus using three complementary methods: lexical, move and dialogic analysis. From a theoretical perspective, this study contributes to improving our understanding of the pervasive phenomenon of emotional labor. From an applied perspective, it offers a new approach for assessing communication practices in various professional contexts.
Bibliographical noteFunding Information:
We would like to thank Georgia Carr (University of Sydney) for acting as independent coder in the lexical analysis reliability test. We are also grateful to the University of Sydney’s School of Literature, Art and Media and the University of Birmingham for funding Matteo Fuoli’s research visit at the Sydney Corpus Lab ( www.sydneycorpuslab.com ) in 2019, which kickstarted this project.
© 2022 Elsevier B.V.
- emotional labor
- language and emotion
- corpus annotation