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India, Coal, Energy transition, Discourse analysis, Text-as-data, Topic modelling, Sentiment analysis, Named entity recognition
Abstract:
India’s coal sector plays a central role in debates on energy transitions, yet systematic evidence on how media frame this transition remains limited. We address this gap by analysing ten years of English-language news coverage using a combined pipeline of dynamic topic modelling, sentiment analysis, and named entity recognition. Across more than 6 thousand articles, we map the evolution of topics, tones, and actor prominence. Environment-related narratives account for only about 13% of coverage, and governance and social issues around 12%, indicating their secondary position in the broader discourse. The energy transition appears largely marginal, typically embedded within frames of coal supply and energy security. Attention spikes around environmental or governance events are short-lived and do not shift narrative weight. Positive tones cluster around topics tied to state and corporate actors emphasising continuity and expansion. We show the coal complex’s discursive dominance and find China to be the most prominent external actor in transition-related coverage. The results provide an evidence-based foundation for subsequent analyses of policy windows and framing strategies around India’s coal phase-down and clean-energy transition.
