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Cited by 465

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Theorizing the image for Security Studies: Visual securitization and the Muhammad Cartoon Crisis

Hansen, Lene·2011·European Journal of International Relations

Abstract

This article provides a framework for the study of visual securitization, that is, when images constitute something or someone as threatened and in need of immediate defense or when securitizing actors argue that images ‘speak security’. To study security politics is to focus on the public constitution of threats and dangers; to study visual securitization, therefore, requires an analysis not just of the image as a free-standing entity, but of the ways it is constituted through spoken and written discourse. To analyze the process of visual securitization, this article advances an inter-visual/intertextual model consisting of four components: the visual itself, its immediate intertextual context, the wider policy discourse, and the constitutions of the image. Three additional sets of theoretical arguments deepen this model by pointing to the specificity of the image as comprised through immediacy, circulability, and ambiguity, the strategies of depiction that images employ, and the genres through which images are brought to the audience. The applicability of the theoretical framework is illustrated through a case study of one of the most conspicuous cases of visual securitization: the Muhammad Cartoon Crisis.

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Metadata

Authors
Hansen, L.
Venue
European Journal of International Relations
Published
2011-01-19
Volume
17
Issue
1
Pages
51-74
ISSN
  • 1354-0661 (ISSN-L)
  • 1460-3713
OpenAlex
W2140128302
Cited by
465
References
44
FWCI
40.72
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Theorizing the image for Security Studies: Visual securitization and the Muhammad Cartoon Crisis. https://app.cochat.ai/papers/10.1177/1354066110388593
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Hansen, L. (2011). Theorizing the image for Security Studies: Visual securitization and the Muhammad Cartoon Crisis. European Journal of International Relations. https://doi.org/10.1177/1354066110388593

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.