PS8-8. Public Perception of Methane Emissions and Climate Change in the Livestock Industry: A Sentiment and Network Analysis of Reddit Discourse (2018–2026).

Abstract

The objective of this study was to analyze public sentiment regarding livestock methane emissions and their perceived impact on climate change through machine learning and network analysis. We sought to quantify prevailing sentiment and identify thematic clusters to understand how the intersection of animal agriculture is perceived by digital communities. The study analyzed a dataset comprising 2,721 Reddit posts collected via the Reddit JSON API, spanning an eight-year period from March 2018 to April 2026. Data collection utilized targeted query strategies focusing on methane, livestock, and greenhouse gas-related keywords. The methodology included a rigorous attrition protocol, involving language filtering and deduplication, and sentiment classification using a multi-model ensemble integrating RoBERTa, ClimateBERT, and VADER. Keyword co-occurrence networks were constructed to identify thematic communities, utilizing the Louvain algorithm for clustering. Temporal analysis was applied across 97 active months to identify trends in discussion volume and sentiment evolution. We found out that overall sentiment is weighted toward the neutral and negative, with 1,306 posts (48.0%) remaining neutral and 1,077 posts (39.6%) expressing negative views regarding livestock emissions. Positive sentiment was identified in only 338 posts (12.4%). Within the thematic clusters, the “Emissions & Climate Science” and “Dairy Farming & Livestock Practices” communities emerged as primary areas of focus, showing high connectivity between keywords such as “methane,” “emissions,” “livestock,” “dairy,” and “carbon.” The most frequent overall keywords were “meat,” “emissions,” “climate,” and “methane.” Temporal trends indicated a statistically significant decrease in sentiment over the study period (p = 0.0025), with major activity spikes recorded in February 2024 and October 2025. While the discourse is largely neutral-to-negative, positive sentiment was specifically linked to keywords such as “sustainability” and “fermentation,” while negative sentiment was driven by concerns surrounding “animal” impacts and “greenhouse gases. We conclude that public perception of the livestock industry's environmental footprint is hardening into a more critical and negative stance over time. The heavy focus on keywords like “emissions” and “mitigation” within the network suggests that users are increasingly focused on the technical and scientific aspects of climate impact. Addressing these concerns through transparent, data-driven communication regarding mitigation technologies is essential for the livestock industry to manage public reputational risks and support the social license to operate in an increasingly climate-conscious digital landscape.