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    A Digital Mixed Methods Research Design: Integrating Multimodal Analysis With Data Mining and Information Visualization for Big Data Analytics

    Access Status
    Fulltext not available
    Authors
    O'Halloran, Kay
    Tan, Sabine
    Pham, DucSon
    Bateman, J.
    Moere, A.
    Date
    2017
    Type
    Journal Article
    
    Metadata
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    Citation
    O'Halloran, K. and Tan, S. and Pham, D. and Bateman, J. and Moere, A. 2017. A Digital Mixed Methods Research Design: Integrating Multimodal Analysis With Data Mining and Information Visualization for Big Data Analytics. Journal of Mixed Methods Research. 12 (1): pp. 11–30.
    Source Title
    Journal of Mixed Methods Research
    DOI
    10.1177/1558689816651015
    ISSN
    1558-6898
    School
    School of Education
    URI
    http://hdl.handle.net/20.500.11937/54657
    Collection
    • Curtin Research Publications
    Abstract

    This article demonstrates how a digital environment offers new opportunities for transforming qualitative data into quantitative data in order to use data mining and information visualization for mixed methods research. The digital approach to mixed methods research is illustrated by a framework which combines qualitative methods of multimodal discourse analysis with quantitative methods of data mining and information visualization in a multilevel, contextual model that will result in an integrated, theoretically well-founded, and empirically evaluated technology for analyzing large data sets of multimodal texts. The framework is applicable to situations in which critical information needs to be extracted from geotagged public data: for example, in crisis informatics, where public reports of extreme events provide valuable data sources for disaster management.

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