A multidimensional analysis of media framing in the Russia-Ukraine war

Majd Ibrahim (), Bang Wang (), Minghua Xu () and Han Xu ()
Additional contact information
Majd Ibrahim: Huazhong University of Science and Technology
Bang Wang: Huazhong University of Science and Technology
Minghua Xu: Huazhong University of Science and Technology
Han Xu: Huazhong University of Science and Technology

Journal of Computational Social Science, 2025, vol. 8, issue 2, No 8, 27 pages

Abstract: Abstract The media plays a crucial role in constructing narratives and shaping public interpretation of global crises, particularly in prolonged geopolitical disputes such as the ongoing war between Russia and Ukraine. Given the significant humanitarian impact of this war, analyzing how it has been framed in the media provides valuable insights into its portrayal and the narratives that emerge over time. While numerous studies have examined media framing of the war, they often focus on isolated events or limited timeframes, overlooking the evolving nature of narratives. This study addresses this gap by conducting a longitudinal framing analysis of war coverage in news media over two years. Unsupervised machine learning models are utilized to explore transformations in volume, narrative themes, and portrayals of the war and its key actors. Our findings contribute to understanding how framing strategies in media coverage shape narratives, with potential implications for public perception and policy discourse. By examining patterns and differences in media framing, this study highlights how distinct editorial priorities influence the portrayal of the war and its broader consequences and potential imbalances in coverage.

Keywords: Russia-Ukraine war; Geopolitical crises; Media framing; News media; Machine learning (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s42001-025-00363-1 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jcsosc:v:8:y:2025:i:2:d:10.1007_s42001-025-00363-1

Ordering information: This journal article can be ordered from
http://www.springer. ... iences/journal/42001

DOI: 10.1007/s42001-025-00363-1

Access Statistics for this article

Journal of Computational Social Science is currently edited by Takashi Kamihigashi

More articles in Journal of Computational Social Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().