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| Type | Working Paper |
| Scope | Discipline-based scholarship |
| Title | A Dataset for Detecting Real-World Environmental Claims |
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| Institution | University of Zurich |
| Series Name | arXiv |
| Number | 2209.00507v1 |
| Date | 2023 |
| Abstract Text | In this paper, we introduce an expert-annotated dataset for detecting real-world environmental claims made by listed companies. We train and release baseline models for detecting environmental claims using this new dataset. We further preview potential applications of our dataset: We use our fine-tuned model to detect environmental claims made in answer sections of quarterly earning calls between 2012 and 2020 -- and we find that the amount of environmental claims steadily increased since the Paris Agreement in 2015. |
| Official URL | https://arxiv.org/abs/2209.00507v1 |
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