Detecting Religious Language in Climate Discourse
This study addresses methodological challenges in digital religious studies for analyzing sacred language in climate debates, but it is incremental as it compares existing methods without introducing a novel paradigm.
This paper tackled the problem of detecting religious language in climate discourse by comparing a rule-based model and large language models on over 880,000 sentences, finding that the rule-based method consistently labeled more sentences as religious than LLMs.
Religious language continues to permeate contemporary discourse, even in ostensibly secular domains such as environmental activism and climate change debates. This paper investigates how explicit and implicit forms of religious language appear in climate-related texts produced by secular and religious nongovernmental organizations (NGOs). We introduce a dual methodological approach: a rule-based model using a hierarchical tree of religious terms derived from ecotheology literature, and large language models (LLMs) operating in a zero-shot setting. Using a dataset of more than 880,000 sentences, we compare how these methods detect religious language and analyze points of agreement and divergence. The results show that the rule-based method consistently labels more sentences as religious than LLMs. These findings highlight not only the methodological challenges of computationally detecting religious language but also the broader tension over whether religious language should be defined by vocabulary alone or by contextual meaning. This study contributes to digital methods in religious studies by demonstrating both the potential and the limitations of approaches for analyzing how the sacred persists in climate discourse.