How English Print Media Frames Human-Elephant Conflicts in India

arXiv cs.CL / 4/24/2026

💬 OpinionIdeas & Deep AnalysisModels & Research

Key Points

  • Human-elephant conflicts in India are increasing due to habitat loss and human settlement expansion, but the study focuses on how English print media frames these conflicts rather than only ecological causes.
  • The research analyzes 1,968 full-length news articles (28,986 sentences) from a major English-language outlet published between January 2022 and September 2025.
  • Using a multi-model sentiment approach (long-context transformers, large language models, and a domain-specific “Negative Elephant Portrayal” lexicon), the study quantifies sentiment and identifies sentences and linguistic patterns that drive negative portrayals.
  • Results show that fear-inducing and aggression-related language dominates coverage, which may shape public attitudes in ways that heighten hostility and weaken coexistence and conservation efforts.
  • The authors provide a transparent, scalable web-scale text analysis methodology and release resources via an anonymized repository to support more responsible wildlife reporting practices.

Abstract

Human-elephant conflict (HEC) is rising across India as habitat loss and expanding human settlements force elephants into closer contact with people. While the ecological drivers of conflict are well-studied, how the news media portrays them remains largely unexplored. This work presents the first large-scale computational analysis of media framing of HEC in India, examining 1,968 full-length news articles consisting of 28,986 sentences, from a major English-language outlet published between January 2022 and September 2025. Using a multi-model sentiment framework that combines long-context transformers, large language models, and a domain-specific Negative Elephant Portrayal Lexicon, we quantify sentiment, extract rationale sentences, and identify linguistic patterns that contribute to negative portrayals of elephants. Our findings reveal a dominance of fear-inducing and aggression-related language. Since the media framing can shape public attitudes toward wildlife and conservation policy, such narratives risk reinforcing public hostility and undermining coexistence efforts. By providing a transparent, scalable methodology and releasing all resources through an anonymized repository, this study highlights how Web-scale text analysis can support responsible wildlife reporting and promote socially beneficial media practices.