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    Interpreting text and image relations in violent extremist discourse: A mixed methods approach for big data analytics

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    Access Status
    Open access
    Authors
    O'Halloran, Kay
    Tan, Sabine
    Wignell, Peter
    Bateman, J.
    Pham, DucSon
    Grossman, M.
    Moere, A.
    Date
    2016
    Type
    Journal Article
    
    Metadata
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    Citation
    O'Halloran, K. and Tan, S. and Wignell, P. and Bateman, J. and Pham, D. and Grossman, M. and Moere, A. 2016. Interpreting text and image relations in violent extremist discourse: A mixed methods approach for big data analytics. Terrorism and Political Violence. 31 (3): pp. 454-474.
    Source Title
    Terrorism and Political Violence
    DOI
    10.1080/09546553.2016.1233871
    ISSN
    0954-6553
    School
    School of Education
    URI
    http://hdl.handle.net/20.500.11937/40551
    Collection
    • Curtin Research Publications
    Abstract

    This article presents a mixed methods approach for analysing text and image relations in violent extremist discourse. The approach involves integrating multimodal discourse analysis with data mining and information visualisation, resulting in theoretically informed empirical techniques for automated analysis of text and image relations in large datasets. The approach is illustrated by a study which aims to analyse how violent extremist groups use language and images to legitimise their views, incite violence, and influence recruits in online propaganda materials, and how the images from these materials are re-used in different media platforms in ways that support and resist violent extremism. The approach developed in this article contributes to what promises to be one of the key areas of research in the coming decades: namely the interdisciplinary study of big (digital) datasets of human discourse, and the implications of this for terrorism analysis and research.

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