LINGUISTIC FRAMING OF THE IRAN-ISRAEL CONFLICT IN THE NEW YORK TIMES AND ALJAZEERA: A COMPARATIVE CORPUS-ASSISTED CRITICAL DISCOURSE ANALYSIS
The current paper examines how the Iran-Israel conflict is linguistically framed in The New York Times and Al Jazeera using a comparative analytical method that involves the use of corpus. The paper particularly investigates the adjectival options that are commonly used and how such lexical patterns can be used to frame semantically and ideologically in media discourse. The study is based on the theory of Frame Semantics by Charles J. Fillmore, and reinforced by thematic analysis, to examine how adjectives trigger more general conceptual frames which influence how political conflict is represented. Two distinct corpora of opinion articles published in 2025-2026 of The New York Times and Al Jazeera are collected and processed with Sketch Engine to find high-frequency adjectives, collocations, and patterns of concordances. The results indicate that The New York Times mostly focuses on the conflict in terms of geopolitical security, nuclear threat, and strategic instability, whereas Al Jazeera tends to focus on militarized politics, regional confrontation, and power imbalance. The comparative analysis also shows that the two newspapers use different semantic framing patterns that help them to make different ideological interpretations of the same geopolitical event. The research shows the important contribution of adjectival framing to media discourse and adds to the comprehension of the impact of linguistic decisions on the ideological representation of political discourse in modern politics. Keywords: Corpus-Assisted Analysis, Frame Semantics, Ideological Positioning, Iran-Israel Conflict, Adjectival Framing, Thematic Analysis
Authors
- Qundeel Fatima
- Ambreen Khalid
- Dr. Muhammad Abdullah
Institutions
- Riphah International University (PK)
Publication Details
- Journal
- Applied Linguistics Research Review
- Published
- 2026-10-06
- Primary Topic
- Cultural and political discourse analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00