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A dataset for detecting real-world environmental claims

Leippold, Markus; Stammbach, Dominik; Webersinke, Nicolas; Bingler, Julia Anna; Kraus, Mathias (2023). A dataset for detecting real-world environmental claims. In: 61st Annual Meeting of the Association for Computational Linguistics (ACL’23), Toronto, Canada, 9 July 2023 - 14 July 2023. arxiv.org, 1-14.

Abstract

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.

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Finance
Dewey Decimal Classification:330 Economics
Scope:Discipline-based scholarship (basic research)
Language:English
Event End Date:14 July 2023
Deposited On:02 Aug 2023 07:53
Last Modified:06 Mar 2024 14:39
Publisher:arxiv.org
OA Status:Green
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.48550/arXiv.2209.00507
Official URL:https://arxiv.org/abs/2209.00507v1
Other Identification Number:merlin-id:23708
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  • Language: English
  • Licence: Creative Commons: Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)

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