Publication: ClimateBERT-NetZero: Detecting and Assessing Net Zero and Reduction Targets
ClimateBERT-NetZero: Detecting and Assessing Net Zero and Reduction Targets
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Schimanski, T., Bingler, J., Kraus, M., Hyslop, C., & Leippold, M. (2023). ClimateBERT-NetZero: Detecting and Assessing Net Zero and Reduction Targets. Proceedings of the Conference on Empirical Methods in Natural Language Processing, 15745–15756. https://doi.org/10.18653/v1/2023.emnlp-main.975
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Public and private actors struggle to assess the vast amounts of information about sustainability commitments made by various institutions. To address this problem, we create a novel tool for automatically detecting corporate and national net zero and reduction targets in three steps. First, we introduce an expert-annotated data set with 3.5K text samples. Second, we train and release ClimateBERT-NetZero, a natural language classifier to detect whether a text contains a net zero or reduction target. Third, we showcase its analysis pot
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- Schimanski, Tobias
- Bingler, Julia
- Kraus, Mathias
- Hyslop, Camilla
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Schimanski, T., Bingler, J., Kraus, M., Hyslop, C., & Leippold, M. (2023). ClimateBERT-NetZero: Detecting and Assessing Net Zero and Reduction Targets. Proceedings of the Conference on Empirical Methods in Natural Language Processing, 15745–15756. https://doi.org/10.18653/v1/2023.emnlp-main.975
