Multimodal Approaches to Media Discourses (Routledge Studies in Multimodality)

ISBN 10: 0367524309 / ISBN 13: 9780367524302

Published by Routledge, 2022

About this Item

Seller Inventory # I-9780367524302

Bibliographic Details

• Title: Multimodal Approaches to Media Discourses (Routledge Studies in Multimodality)
• Publisher: Routledge
• Publication Date: 2022
• Language: English
• ISBN 10: 0367524309
• ISBN 13: 9780367524302
• Binding: Soft cover
• Condition: New

About this title

Synopsis

Multimodal Approaches to Media Discourses brings together contributions from an interdisciplinary group of scholars on corpus-assisted analyses of multimodal data on austerity discourses in the United Kingdom, which extend and expand on the understanding of austerity but also of the methodologies used to analyse multimodal corpora.

The volume demonstrates how the austerity measures introduced in response to global economic and financial crises in recent years can be viewed as being more complexly layered than they appear, not simply reduced to their connections to spending cuts and fiscal debt. The book employs an innovative methodological approach, in which established and emerging scholars from linguistics and computational and social sciences critically reflect on the exact same set of data – multimodal texts and articles from The Guardian and The Daily Telegraph from 2010 to 2016. This framework allows for the exploration of the role of the media in mediating the public’s assessment of austerity and the ideas, actors, emotions, geographies and broader material context which contribute to such perceptions. In so doing, the volume also offers unique insights into systematic analyses to multimodal data which may be applied to other topics and connected with other disciplines.

Enhancing our awareness and assessment of austerity in public discourse and of the methodologies to study it, this book is key reading for students and researchers in discourse analysis, corpus linguistics, multimodality, and those working at the intersection of these fields.

About the Author

Tim Griebel is a former assistant professor at the Institute of Political Science at Friedrich-Alexander-Universität

Erlangen-Nürnberg (FAU), Germany.

Stefan Evert is the chair of Computational Corpus Linguistics at Friedrich-Alexander-Universität

Erlangen-Nürnberg (FAU), Germany.

Philipp Heinrich is a PhD candidate in Corpus and Computational Linguistics at Friedrich-Alexander-Universität

Erlangen-Nürnberg (FAU), Germany.