Performing leadership: international politics through the lens of visual narrative analysis

IF 1.8 Q2 POLITICAL SCIENCE
Katja Freistein, Frank Gadinger
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引用次数: 2

Abstract

ABSTRACT Since visuality in the (self-)representation of politicians and other influential figures has become an important part of political storytelling, we propose to use visual narrative analysis (VNA) as a systematic approach for its better understanding. VNA is particularly suited for this performative strand of interpretive analysis, as it does not study images in isolation but in the broader context of political narratives. By analysing different layers of communication (images, narratives, competing narratives) VNA enables us to identify internal contradictions that undermine political efforts of self-representation in contexts of global governance (e.g. multilateral diplomacy) and render them unstable and contestable. By analysing competing (self-)representations at a G7 meeting in 2018, we show how VNA can be applied fruitfully to the study of international politics and, second, how VNA can explain some of the reasons why one image became iconic (Angela Merkel as female leader of the liberal world), i.e. appealed to a wider audience, and others (focusing on Emmanuel Macron or Donald Trump) did not. While our article is primarily a demonstration of the methodological benefits of VNA for various research contexts in world politics, it also contributes to conceptual debates on the combination of visuality, narratives and emotions in changing practices of political storytelling.
执行领导:透过视觉叙事分析的镜头看国际政治
由于政治家和其他有影响力的人物(自我)表征中的视觉性已经成为政治叙事的重要组成部分,我们提出使用视觉叙事分析(VNA)作为一种系统的方法来更好地理解它。VNA特别适合这种解释性分析的表演链,因为它不是孤立地研究图像,而是在更广泛的政治叙事背景下研究图像。通过分析不同层次的传播(图像、叙事、竞争叙事),越南新闻社使我们能够识别内部矛盾,这些矛盾破坏了在全球治理背景下(如多边外交)自我代表的政治努力,并使其不稳定和有争议。通过分析2018年七国集团(G7)会议上相互竞争的(自我)表述,我们展示了越通社如何有效地应用于国际政治研究,其次,越通社如何解释为什么一个形象成为标志性(安格拉·默克尔作为自由世界的女性领导人),即吸引更广泛的受众,而其他形象(关注埃马纽埃尔·马克龙或唐纳德·特朗普)却没有。虽然我们的文章主要展示了VNA在世界政治各种研究背景下的方法论优势,但它也有助于在不断变化的政治叙事实践中结合视觉,叙事和情感的概念辩论。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Political Research Exchange
Political Research Exchange POLITICAL SCIENCE-
CiteScore
3.40
自引率
0.00%
发文量
25
审稿时长
39 weeks
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