AICLCYApr 23

How English Print Media Frames Human-Elephant Conflicts in India

arXiv:2604.2149645.8h-index: 10
Predicted impact top 77% in AI · last 90 daysOriginality Incremental advance
AI Analysis

For conservationists and policymakers, this work highlights how media framing of human-elephant conflict can shape public attitudes and potentially hinder coexistence efforts.

This study presents the first large-scale computational analysis of media framing of human-elephant conflict in India, analyzing 1,968 news articles. It finds a dominance of fear-inducing and aggression-related language that could reinforce public hostility and undermine coexistence efforts.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes