mlsanityData to 7 Oct 2026

Analysis of Climate Campaigns on Social Media using Bayesian Model Averaging

arXiv 2305.06174 ↗First posted 6 May 2023cs.CL cs.AI cs.CYcited by 3

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Abstract (arXiv)

Climate change is the defining issue of our time, and we are at a defining moment. Various interest groups, social movement organizations, and individuals engage in collective action on this issue on social media. In addition, issue advocacy campaigns on social media often arise in response to ongoing societal concerns, especially those faced by energy industries. Our goal in this paper is to analyze how those industries, their advocacy group, and climate advocacy group use social media to influence the narrative on climate change. In this work, we propose a minimally supervised model soup [57] approach combined with messaging themes to identify the stances of climate ads on Facebook. Finally, we release our stance dataset, model, and set of themes related to climate campaigns for future work on opinion mining and the automatic detection of climate change stances.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 26 of its 62 references that are in the map. First posted on arXiv 6 May 2023.

Builds on

26 of 62 references.

References · 26

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14 more
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Cited by year

Citing papers per year: 2024: 2; 2025: 1.

3 papers.

  1. 2024Uncovering Latent Arguments in Social Media Messaging by Employing LLMs-in-the-Loop Strategycited by 9
  2. 2025Can LLMs Assist Annotators in Identifying Morality Frames? -- Case Study on Vaccination Debate on Social Mediacited by 1
  3. 2024Effects of Collaboration on the Performance of Interactive Theme Discovery Systemscited by 0