Enhancing Online Climate Discourse

A Two-Stage Framework for Climate Content Categorization and Moderation

authored by

Apoorva Upadhyaya, Wolfgang Nejdl, Marco Fisichella

Abstract

Climate change is one of the most pressing global challenges that requires urgent adaptation and resilience efforts, highlighting the need for both scientific solutions and effective communication. In the digital age, online content plays a key role in shaping climate narratives. Therefore, previous research has mainly focused on public perception or categorized content by topics such as impacts, mitigation, policy, etc. Despite these efforts, identifying discussions that address climate change adaptation is crucial for monitoring resilience and assessing public sentiment, while recognizing denial narratives helps combat misinformation. Moreover, the public's exposure to online climate content can either lead to or hinder climate action, emphasizing the need for climate content moderation. To address these issues, we propose a novel multistage framework where stage 1 categorizes climate-related content into adaptation, resilience, and denial while stage 2 moderates content by enhancing or intervening based on its alignment with climate goals. We present a novel dataset by manually annotating publicly available tweets and news articles into different climate categories with the help of a taxonomy developed by domain experts. Extensive experiments with benchmark climate and other domain datasets validate the efficacy of our prediction stage, while human and external evaluations confirm the relevance of our moderation stage.

Organisation(s)

L3S Research Centre

Type

Conference contribution

Pages

9890-9898

No. of pages

9

Publication date

2025

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Artificial Intelligence

Sustainable Development Goals

SDG 13 - Climate Action

Electronic version(s)

https://doi.org/10.24963/ijcai.2025/1099 (Access: Closed)