Publication: Environmental Claim Detection
Environmental Claim Detection
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Leippold, M., Stammbach, D., Webersinke, N., Bingler, J. A., & Kraus, M. (2023). Environmental Claim Detection. Proceedings of the Annual Meeting of the Association for Computational Linguistics, 1051–1066. https://doi.org/10.18653/v1/2023.acl-short.91
Abstract
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To transition to a green economy, environmental claims made by companies must be reliable, comparable, and verifiable. To analyze such claims at scale, automated methods are needed to detect them in the first place. However, there exist no datasets or models for this. Thus, this paper introduces the task of environmental claim detection. To accompany the task, we release an expert-annotated dataset and models trained on this dataset. We preview one potential application of such models: We detect environmental claims made in quarterly
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Creators (Authors)
- Stammbach, Dominik
- Webersinke, Nicolas
- Bingler, Julia Anna
- Kraus, Mathias
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Leippold, M., Stammbach, D., Webersinke, N., Bingler, J. A., & Kraus, M. (2023). Environmental Claim Detection. Proceedings of the Annual Meeting of the Association for Computational Linguistics, 1051–1066. https://doi.org/10.18653/v1/2023.acl-short.91
