The article examines the linguistic and discursive mechanisms through which humanitarian suffering is constructed in digital news texts about the war in Gaza within the broader context of the Palestinian-Israeli conflict. The analysis focuses on victim nomination, the lexicon of pain, hunger, destruction, and loss, patterns of agency distribution, passive constructions, evaluative vocabulary, and source hierarchy in materials published by BBC, CNN, Al Jazeera, RT, and RIA Novosti in 2023–2025. The material consists of 30 comparable digital texts and textual news materials selected from thematic clusters in which humanitarian suffering constitutes the central rather than peripheral focus: blockade, hospitals, aid distribution, mass displacement, hunger, and attacks on camps and humanitarian facilities. The methodology combines comparative discourse analysis, lexical-semantic analysis, qualitative media text analysis, and manual coding according to four parameters: victim nomination, semantic fields of suffering, grammatical agency, and source attribution. The novelty of the study lies in clarifying the concept of the humanitarian register of digital news text and in comparing not broad political or ideological frames, but micro-level linguistic mechanisms through which humanitarian suffering is transformed into a media event. The findings show that Al Jazeera most consistently foregrounds witness-based and emotionally concentrated representation, while this affective density also requires critical interpretation; BBC and CNN combine humanitarian vocabulary with multi-source attribution, yet institutional caution and source symmetry may weaken direct agency; RT correlates humanitarian issues with event-centered, conflict-related, and foreign-policy contexts, emphasizing competing interpretations and responsibility; RIA Novosti more often presents humanitarian issues through institutional-statistical and logistical description, which stabilizes documentary reporting and limits excessive emotionalization.
Fadi Saket Awad Alazzeh (Wed,) studied this question.