Conference proceeding
Towards Designing Social Interventions for Online Climate Change Denialism Discussions
Proceedings of the ACM on human-computer interaction, v 9(7), pp 1-24
16 Oct 2025
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
As conspiracy theories gain traction, it has become crucial to research effective intervention strategies that can foster evidence and science-based discussions in conspiracy theory communities online. This study presents a novel framework using insider language to contest conspiracy theory ideology in climate change denialism on Reddit. Focusing on discussions in two Reddit communities, our research investigates reactions to pro-social and evidence-based intervention messages for two cohorts of users: climate change deniers and climate change supporters. Specifically, we combine manual and generative AI-based methods to craft intervention messages and deploy the interventions as replies on Reddit posts and comments through transparently labeled bot accounts. On the one hand, we find that evidence-based interventions with neutral language foster positive engagement, encouraging open discussions among believers of climate change denialism. On the other, climate change supporters respond positively, actively participating and presenting additional evidence. Our study contributes valuable insights into the process and challenges of automatically delivering interventions in conspiracy theory communities on social media, and helps inform future research on social media interventions.
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Details
- Title
- Towards Designing Social Interventions for Online Climate Change Denialism Discussions
- Creators
- Ruican Zhong - University of Washington, Seattle, WA, USAShruti Phadke - Drexel University, Information ScienceBeth Goldberg - Jigsaw (Google), New York, NY, USATanushree Mitra - University of Washington
- Publication Details
- Proceedings of the ACM on human-computer interaction, v 9(7), pp 1-24
- Publisher
- Association for Computing Machinery
- Number of pages
- 24
- Grant note
Research reported in this publication was supported by Google Jigsaw. We would also like to thank Neelesh Azad for helping us with the experimental design that supported the methodology write-up of the paper.
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:001615106100001
- Scopus ID
- 2-s2.0-105019064496
- Other Identifier
- 991022122860004721
UN Sustainable Development Goals (SDGs)
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Source: SDGs in the Output
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Computer Science, Cybernetics
- Computer Science, Information Systems