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dc.contributor.authorO'Halloran, Kay
dc.contributor.authorE, M.K.L.
dc.contributor.authorTan, Sabine
dc.contributor.editorJewitt, C.
dc.date.accessioned2017-03-15T22:05:53Z
dc.date.available2017-03-15T22:05:53Z
dc.date.created2017-02-24T00:09:12Z
dc.date.issued2014
dc.identifier.citationO'Halloran, K. and E, M.K.L. and Tan, S. 2014. Multimodal analytics: Software and visualization techniques for analyzing and interpreting multimodal data, in Jewitt, C. (ed), The Routledge Handbook of Multimodal Analysis, pp. 386-396. United Kingdom: Routledge.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/49563
dc.description.abstract

Multimodal analysis, the study of semantic patterns arising from the integration of language, images and audio resouces in multimodal texts, presents considerable challenges which are both theoretical and practical in nature. First, frameworks for modeling the semantic contributions of the different resources and the meaning arising from the interaction of choices in multimodal phenomena are required. Such frameworks also need to account for resemioticization of mulitmodal phenomena to investigate social practices over space and time (Iedema, 2001, 2003). In this repect, the social semiotic approach (Halliday, 1978; Halliday and Matthiese4n, 2004) developed by Kress and Van Leeuwen (2005 [1996] and O'Toole (2011 [1994]) has provided a powerful theoretical platform for investigating multimodal phenomena (eg. see this volume)

dc.publisherRoutledge
dc.titleMultimodal analytics: Software and visualization techniques for analyzing and interpreting multimodal data
dc.typeBook Chapter
dcterms.source.startPage386
dcterms.source.endPage396
dcterms.source.titleThe Routledge Handbook of Multimodal Analysis
dcterms.source.isbn9780415519748
dcterms.source.placeUnited Kingdom
dcterms.source.chapter34
curtin.departmentSchool of Education
curtin.accessStatusFulltext not available


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