Beyond peace journalism

Keren Tenenboim-Weinblatt, Thomas Hanitzsch and Rotem Nagar
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Keren Tenenboim-Weinblatt: Department of Communication and Journalism, Hebrew University of Jerusalem
Thomas Hanitzsch: Institute of Communication Studies and Media Research, LMU Munich
Rotem Nagar: Department of Communication and Journalism, Hebrew University of Jerusalem

Journal of Peace Research, 2016, vol. 53, issue 2, 151-165

Abstract: This article presents a general framework for deconstructing and classifying conflict news narratives. This framework, based on a nuanced and contextual approach to analyzing media representations of conflict actors and events, addresses some of the weaknesses of existing classification schemes, focusing in particular on the dualistic approach of the peace journalism model. Using quantitative content analysis, the proposed framework is then applied to the journalistic coverage in the Israeli media of three Middle-Eastern conflicts: the Israeli–Palestinian conflict, the conflict surrounding Iran's nuclear program, and the Syrian civil war. The coverage is examined in three leading news outlets – Haaretz , Israel Hayom , and Ynet – over a six-month period. Based on hierarchical cluster analysis, the article identifies four characteristic types of narratives in the examined coverage. These include two journalistic narratives of violence: one inward-looking, ethnocentric narrative, and one outward-looking narrative focusing on outgroup actors and victims; and two political-diplomatic narratives: one interactional, and one outward-looking. In addition to highlighting different constellations of points of view and conflict measures in news stories, the identified clusters also challenge several assumptions underlying existing models, such as the postulated alignment between elite/official actors and violence frames

Keywords: narratives; news; peace journalism (search for similar items in EconPapers)
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:sae:joupea:v:53:y:2016:i:2:p:151-165

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