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Mixed-methods analysis reveals algorithmic segregation of visual narratives in Instagram posts about the Al-Ahli Baptist Hospital massacre, highlighting decolonization challenges.
On October 17, 2023, Al-Ahli Baptist Hospital explosion in Gaza became a global visual event, circulating rapidly across Instagram before official narratives stabilized. This crisis exemplified the contemporary complexities of platformed affective witnessing. While graphic footage, forensic maps, and institutional denials circulated simultaneously, it remains underexplored how platform algorithms, visual affordances, and geopolitical ideologies intersect to govern crisis visibility and epistemic authority. Addressing this gap, this research endeavor employs a mixed-methods analytical framework. Synergizing computer vision, network mapping, seeded topic modeling, and discursive news values analysis, it analyzes a macro-dataset of 10,432 images and a micro-corpus of 300 ideologically stratified Instagram posts from Al Jazeera , The New York Times , and the Israeli Defense Forces (IDF) . Findings reveal that Instagram does not facilitate a shared public sphere; rather, audiences are algorithmically segregated into three distinct visual regimes: trauma-centric hypervisibility , forensic spatiality , and strategic erasure . These regimes dynamically calibrate proximity, affect, and credibility (weaponizing both hyper-visibility and strategic absence) to mediate solidarity, skepticism, and institutional exoneration. The study exposes an enduring algorithmic asymmetry in digital conflict reporting, demonstrating that while decolonial digital practices enable Global South testimonies to achieve hypervisibility, they remain structurally subjected to epistemic suspicion and delegitimization.
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Nashwa Elyamany (2026) studied this question.
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