Wild Conversations: Comparing Media Narratives on Comeback Species in Europe Through Computational Text Analysis

Summary

Across Europe, wildlife species are making comebacks. While these returns are celebrated as milestones for biodiversity, they spark public debates. This study investigates newspaper narratives of five comeback species (badgers, beavers, otters, lynxes, and wolves) in four European countries (Germany, the Netherlands, Switzerland, and the United Kingdom), in three different languages (German, Dutch, and English) to quantitatively measure and compare how these species are presented in public media arena over the last 24 years. Upon the corpus building from newspaper articles, we apply multilingual natural language processing, including sentiment analysis and corpus linguistics approach. The result showed the corpus size to represent the species population to some extent, yet the species that spark political disputes, exemplified by wolves, garnered disproportionately high attention. Sentiment analysis revealed a persistent prevalence of negative sentiment toward comeback species, except for beavers in the UK. By employing corpus linguistics with word co-occurrence analysis, we identified key actors, perceived benefits and damages, and managerial actions associated with the species. This semantic retrieval led to cross-species comparisons, such as species of different sentiment (i.e. negative badgers and positive beavers in the UK), and cross-comparisons of wolves in different countries (i.e. Germany, the Netherlands, and Switzerland). Our scalable and comparative approach demonstrates the utility of computational methods in unravelling sociocultural and political context behind biodiversity narratives in the media, which can offer valuable insights and lessons for designing context-specific conservation interventions for biodiversity and conservation policy.