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Same, same but different? A Discourse Network Analysis of the EU's framings of refugee arrivals in 2015 and 2022.
J Ethn Migr Stud
November 2024
Institute for Sociology, University of Duisburg Essen, Duisburg, Germany.
The European Union (EU) experienced two major instances of refugee influx: in 2015, refugees, mainly from Syria, Afghanistan and Iraq fled civil war, persecution, and dire conditions in neighbouring countries and in 2022, Ukrainians fled from Russia's full-scale invasion. Fusing theoretical insights on framing and crisification of migration, we ask: How do EU actors frame situations of refugee mass influx? Employing a Discourse Network Analysis, we examine EU representatives' framing of both instances with respect to three analytical foci: (1) who or what they considered to be in crisis, (2) their framing of refugees; and (3) who they saw to be responsible for solving the crisis. We show how, in 2015, EU representatives framed mass displacement predominantly as a crisis at and of Europe's borders, and refugees as threats to Member States' public, economic and cultural security.
View Article and Find Full Text PDFEvaluating the role of generative AI and color patterns in the dissemination of war imagery and disinformation on social media.
Front Artif Intell
January 2025
Alma Sistemi Srl, Rome, Italy.
This study explores the evolving role of social media in the spread of misinformation during the Ukraine-Russia conflict, with a focus on how artificial intelligence (AI) contributes to the creation of deceptive war imagery. Specifically, the research examines the relationship between color patterns (LUTs) in war-related visuals and their perceived authenticity, highlighting the economic, political, and social ramifications of such manipulative practices. AI technologies have significantly advanced the production of highly convincing, yet artificial, war imagery, blurring the line between fact and fiction.
View Article and Find Full Text PDFApplication of the DRASTIC Model to Assess the Vulnerability of Groundwater Contamination Near Zaporizhzhia Nuclear Power Plant, Ukraine.
ACS ES T Water
January 2025
Lawrence Livermore National Laboratory, Livermore, California 94550, United States.
Russia's invasion of Ukraine continues to have a devastating effect on the well-being of Ukrainians and their environment. We evaluated a major environmental hazard caused by the war: the potential for groundwater contamination in proximity to the Zaporizhzhia Nuclear Power Plant (NPP). We quantified groundwater vulnerability with the DRASTIC index, which was originally developed by the United States Environmental Protection Agency and has been used at various locations worldwide to assess relative pollution potential.
View Article and Find Full Text PDFThe effect of conflict on damage to medical facilities in Mariupol, Ukraine: A quasi-experimental study.
PLOS Glob Public Health
January 2025
Epidemiology of Microbial Diseases Department, Yale Humanitarian Research Lab, Yale School of Public Health, New Haven, Connecticut, United States of America.
Medical facilities are civilian objects specially protected by international humanitarian law. Despite the need for systematic documentation of the effects of war on medical facilities for judiciary accountability, current methods for surveilling damage to protected civilian objects during ongoing armed conflict are insufficient. Satellite imagery damage assessment confers significant possibilities for investigating patterns of war.
View Article and Find Full Text PDFNexus of crude oil and clean energy stock indices: Evidence from time-vector-auto-regression in conjunction with conditional-autoregressive-value-at-risk.
Heliyon
January 2025
Faculty of Economics and Management of Sfax, University of Sfax, Tunisia.
The current study aims to elicit information regarding the tail risk transmission mechanism between crude oil (CO) and selected clean energy (CE) stock indices across time and during certain economic events. A Time-Varying Parameter Vector Auto-Regressive model (TVP-VAR) paired with the conditional autoregressive value-at-risk (CAViaR) approach was used to investigate data from January 1, 2015 to December 29, 2022. Overall, we show that an increased vulnerability to tail risk and deficits might be linked to dynamic spillover over examined markets.
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