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<p>This study applies and extends Keymorph Analysis (KMA) with cognitive linguistic theory to investigate the representation of the Israeli–Palestinian conflict in Russia Today (RT)’s Russian-language headlines. Unlike traditional keyword analysis, which primarily focuses on lexical content, KMA reveals underlying narrative orientations by examining how systematic morphosyntactic choices contribute to the construal of participant roles. Our approach integrates three analytical layers: (1) a Quantitative Layer that identifies statistically significant keymorphs using a novel dual-reference framework (Standardized Residuals for internal distinctiveness and Log-likelihood tests against a broad reference corpus) via LLM-enhanced annotation (98.58% accuracy); (2) a Contextual Analysis Layer that maps these grammatical patterns to their specific lexical and semantic environments through corpus-assisted analysis; and (3) a Cognitive-Semantic Interpretation Layer grounded in the cognitive-semantic networks of the Russian case system. Through this integrated analysis, we identify a core-periphery hierarchy in case usage, revealing three contrastive cognitive schemas: military agents vs. humanitarian space, active entities vs. constrained subjects, and external dominance vs. regional passivity. Ultimately, this study provides a scalable, LLM-enhanced methodology for analyzing morphologically rich languages, advancing our understanding of how grammatical case assignment functions as a systematic mechanism for organizing participant positioning and constructing divergent narrative framings.</p>

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LLM-assisted keymorph analysis of grammatical case in RT’s Israeli–Palestinian conflict coverage

  • 期刊论文

  • 发表日期：

    2026年6月3日

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  • Tingting Lu

摘要

This study applies and extends Keymorph Analysis (KMA) with cognitive linguistic theory to investigate the representation of the Israeli–Palestinian conflict in Russia Today (RT)’s Russian-language headlines. Unlike traditional keyword analysis, which primarily focuses on lexical content, KMA reveals underlying narrative orientations by examining how systematic morphosyntactic choices contribute to the construal of participant roles. Our approach integrates three analytical layers: (1) a Quantitative Layer that identifies statistically significant keymorphs using a novel dual-reference framework (Standardized Residuals for internal distinctiveness and Log-likelihood tests against a broad reference corpus) via LLM-enhanced annotation (98.58% accuracy); (2) a Contextual Analysis Layer that maps these grammatical patterns to their specific lexical and semantic environments through corpus-assisted analysis; and (3) a Cognitive-Semantic Interpretation Layer grounded in the cognitive-semantic networks of the Russian case system. Through this integrated analysis, we identify a core-periphery hierarchy in case usage, revealing three contrastive cognitive schemas: military agents vs. humanitarian space, active entities vs. constrained subjects, and external dominance vs. regional passivity. Ultimately, this study provides a scalable, LLM-enhanced methodology for analyzing morphologically rich languages, advancing our understanding of how grammatical case assignment functions as a systematic mechanism for organizing participant positioning and constructing divergent narrative framings.