Tschirky, Michael; Makhortykh, Mykola (2023). #Azovsteel: Comparing qualitative and quantitative approaches for studying framing of the siege of Mariupol on Twitter. Media, war & conflict, 17(2), pp. 163-178. Sage 10.1177/17506352231184163
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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.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
03 Faculty of Business, Economics and Social Sciences > Social Sciences > Institute of Communication and Media Studies (ICMB) |
UniBE Contributor: |
Tschirky, Michael Stefan, Makhortykh, Mykola |
Subjects: |
000 Computer science, knowledge & systems > 070 News media, journalism & publishing 300 Social sciences, sociology & anthropology 300 Social sciences, sociology & anthropology > 320 Political science |
ISSN: |
1750-6352 |
Publisher: |
Sage |
Language: |
English |
Submitter: |
Mykola Makhortykh |
Date Deposited: |
13 Nov 2023 14:08 |
Last Modified: |
16 Jun 2024 02:19 |
Publisher DOI: |
10.1177/17506352231184163 |
Uncontrolled Keywords: |
Ukraine, Russia, war, Azov, Mariupol, framing, Twitter, methodology, comparative analysis, topic modeling, news frames |
BORIS DOI: |
10.48350/188804 |
URI: |
https://boris.unibe.ch/id/eprint/188804 |
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