ClimateBERT-NetZero: Detecting and Assessing Net Zero and Reduction Targets

Schimanski T, Bingler J, Hyslop C, Kraus M, Leippold M (2023)

Publication Type: Conference contribution

Publication year: 2023

Publisher: Association for Computational Linguistics (ACL)

Pages Range: 15745-15756

Conference Proceedings Title: EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings

Event location: Singapore SG

ISBN: 9798891760608

Abstract

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, national, and regional 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 potential with two use cases: We first demonstrate how ClimateBERT-NetZero can be combined with conventional question-answering (Q&A) models to analyze the ambitions displayed in net zero and reduction targets. Furthermore, we employ the ClimateBERT-NetZero model on quarterly earning call transcripts and outline how communication patterns evolve over time. Our experiments demonstrate promising pathways for extracting and analyzing net zero and emission reduction targets at scale.

Authors with CRIS profile

Mathias Kraus Juniorprofessur für Data Analytics

Involved external institutions

University of Zurich / Universität Zürich (UZH) CH Switzerland (CH) University of Oxford GB United Kingdom (GB)

How to cite

APA:

Schimanski, T., Bingler, J., Hyslop, C., Kraus, M., & Leippold, M. (2023). ClimateBERT-NetZero: Detecting and Assessing Net Zero and Reduction Targets. In Houda Bouamor, Juan Pino, Kalika Bali (Eds.), EMNLP 2023 - 2023 Conference on Empirical Methods in Natural Language Processing, Proceedings (pp. 15745-15756). Singapore, SG: Association for Computational Linguistics (ACL).

MLA:

Schimanski, Tobias, et al. "ClimateBERT-NetZero: Detecting and Assessing Net Zero and Reduction Targets." Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023, Singapore Ed. Houda Bouamor, Juan Pino, Kalika Bali, Association for Computational Linguistics (ACL), 2023. 15745-15756.

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