3.8 Article

#Azovsteel: Comparing qualitative and quantitative approaches for studying framing of the siege of Mariupol on Twitter

Journal

MEDIA WAR AND CONFLICT
Volume -, Issue -, Pages -

Publisher

SAGE PUBLICATIONS LTD
DOI: 10.1177/17506352231184163

Keywords

framing; Mariupol; methodology; Twitter; Ukraine; war

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Social media platforms play a crucial role in shaping public perception of contemporary wars, including the ongoing Russian invasion of Ukraine. However, studying how these platforms represent violence and the aspects that users emphasize presents multiple challenges. The authors compare qualitative content analysis and topic modeling to investigate the framing of the siege of Mariupol in 2022 on Twitter during the Russian-Ukrainian war. Their findings reveal similarities in the prevalence of human interest and conflict frames, consistent with previous research, but also identify differences in the visibility of less common frames such as morality and responsibility, depending on the method used.
Social media platforms play a major role in shaping how the public around the world perceives contemporary wars, including the ongoing Russian invasion of Ukraine. However, there are multiple challenges in studying how exactly these platforms represent violence and what aspects of it are made more salient by their users. One of these challenges concerns the broad range of qualitative and quantitative approaches used to study platform-based war framing and their different capabilities in tackling the large volume of available data. To address this challenge, the authors compare the performance of qualitative and quantitative approaches - i.e. qualitative content analysis and topic modelling - for studying how one of the key episodes of the Russian-Ukrainian war, the siege of Mariupol in 2022 was framed on Twitter over time. Their findings demonstrate that both approaches show the prevalence of human interest and conflict frames that aligns with earlier research on war framing in journalistic media. At the same time, they observe differences in the estimated visibility of less common frames, such as morality and responsibility frames, depending on what method is used.

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