Decoding Climate Disagreement: A Graph Neural Network-Based Approach to Understanding Social Media Dynamics

Ruiran Su, Janet B. Pierrehumbert
7/9/2024
cs.CL

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Abstract

This work introduces the ClimateSent-GAT Model, an innovative method that integrates Graph Attention Networks (GATs) with techniques from natural language processing to accurately identify and predict disagreements within Reddit comment-reply pairs. Our model classifies disagreements into three categories: agree, disagree, and neutral. Leveraging the inherent graph structure of Reddit comment-reply pairs, the model significantly outperforms existing benchmarks by capturing complex interaction patterns and sentiment dynamics. This research advances graph-based NLP methodologies and provides actionable insights for policymakers and educators in climate science communication.

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Cite this paper

@article{su2024decoding,
  title  = {Decoding Climate Disagreement: A Graph Neural Network-Based Approach to Understanding Social Media Dynamics},
  author = {Ruiran Su and Janet B. Pierrehumbert},
  year   = {2024},
  eprint = {2407.07038},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2407.07038v1}
}

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