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Learning from linguistics: rethinking multimodal enquiry

Learning from linguistics: rethinking multimodal enquiry

Kohrs, Kirsten (2017) Learning from linguistics: rethinking multimodal enquiry. International Journal of Social Research Methodology, 21 (1). pp. 49-61. ISSN 1364-5579 (Print), 1464-5300 (Online) (doi:https://doi.org/10.1080/13645579.2017.1321259)

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Abstract

Multimodal studies posit that meaning is not only communicated through spoken and written words, but also through other modes such as images, gesture, gaze, proximity etc. The widespread availability of high-quality, miniaturised audio and video recording and storing technology has made multimodal data collection cheap and easy. However, the transcription and analysis of the resulting avalanche of recorded data is complex, time-consuming, labour-intensive and expensive. To date there is no established practice or consensus as to scope, methods, objectives or definitions. In fact, concern has been voiced that the field risks expanding to the point of incoherence, sometimes building theory from intuition and generalising from single case studies. Lessons from the 200-year-old discipline of modern linguistics can provide one way forward for the vibrant emerging field of multimodal studies by introducing methods that generate results and hypotheses which can be critically evaluated and empirically tested.

Item Type: Article
Additional Information: The author's manuscript uploaded here is embargoed until November 11, 2018. To quote from the article go to the online publication at http://www.tandfonline.com/doi/abs/10.1080/13645579.2017.1321259?journalCode=tsrm20
Uncontrolled Keywords: Corpus linguistics, Cross-disciplinary methodology, Linguistics, Multimodality, Semiotics, Theory, Visual communication
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Department of Marketing, Events & Tourism
Last Modified: 11 Nov 2018 01:38
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: GREAT a
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/17486

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