Decoding climate agreement: a graph neural network-based approach to understanding climate dynamics
This paper presents the ClimateSent-GAT Model, a novel approach that combines Graph Attention Networks (GATs) with natural language processing techniques to accurately identify and predict disagreements within Reddit comment-reply pairs. Our model classifies disagreements into three categories: agre...
| Main Authors: | , |
|---|---|
| Format: | Conference item |
| Language: | English |
| Published: |
Association for Computational Linguistics
2024
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| _version_ | 1811140961946828800 |
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| author | Su, R Pierrehumbert, J |
| author_facet | Su, R Pierrehumbert, J |
| author_sort | Su, R |
| collection | OXFORD |
| description | This paper presents the ClimateSent-GAT
Model, a novel approach that combines Graph
Attention Networks (GATs) with natural language processing techniques 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. |
| first_indexed | 2024-09-25T04:30:18Z |
| format | Conference item |
| id | oxford-uuid:d49e41ec-8f06-4afe-97b0-6070905d1a84 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-09-25T04:30:18Z |
| publishDate | 2024 |
| publisher | Association for Computational Linguistics |
| record_format | dspace |
| spelling | oxford-uuid:d49e41ec-8f06-4afe-97b0-6070905d1a842024-08-27T10:41:04ZDecoding climate agreement: a graph neural network-based approach to understanding climate dynamicsConference itemhttp://purl.org/coar/resource_type/c_5794uuid:d49e41ec-8f06-4afe-97b0-6070905d1a84EnglishSymplectic ElementsAssociation for Computational Linguistics2024Su, RPierrehumbert, JThis paper presents the ClimateSent-GAT Model, a novel approach that combines Graph Attention Networks (GATs) with natural language processing techniques 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. |
| spellingShingle | Su, R Pierrehumbert, J Decoding climate agreement: a graph neural network-based approach to understanding climate dynamics |
| title | Decoding climate agreement: a graph neural network-based approach to understanding climate dynamics |
| title_full | Decoding climate agreement: a graph neural network-based approach to understanding climate dynamics |
| title_fullStr | Decoding climate agreement: a graph neural network-based approach to understanding climate dynamics |
| title_full_unstemmed | Decoding climate agreement: a graph neural network-based approach to understanding climate dynamics |
| title_short | Decoding climate agreement: a graph neural network-based approach to understanding climate dynamics |
| title_sort | decoding climate agreement a graph neural network based approach to understanding climate dynamics |
| work_keys_str_mv | AT sur decodingclimateagreementagraphneuralnetworkbasedapproachtounderstandingclimatedynamics AT pierrehumbertj decodingclimateagreementagraphneuralnetworkbasedapproachtounderstandingclimatedynamics |