Detecting Greenwashing in ESG Reports: A Comparative Analysis of Machine Learning Methods in Traffic-Related Emissions Disclosure

Johannes Florstedt, Jonas Fahlbusch, Moritz Sontheimer


Anthology ID:
2025.swisstext-1.3
Volume:
Proceedings of the 10th edition of the Swiss Text Analytics Conference
Month:
May
Year:
2025
Address:
Winterthur, Switzerland
Editors:
Jonathan Gerber, Mark Cieliebak, Don Tuggener, Manuela Hürlimann
Venue:
SwissText
SIG:
SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
25–30
Language:
URL:
https://aclanthology.org/2025.swisstext-1.3/
DOI:
Bibkey:
Cite (ACL):
Johannes Florstedt, Jonas Fahlbusch, and Moritz Sontheimer. 2025. Detecting Greenwashing in ESG Reports: A Comparative Analysis of Machine Learning Methods in Traffic-Related Emissions Disclosure. In Proceedings of the 10th edition of the Swiss Text Analytics Conference, pages 25–30, Winterthur, Switzerland. Association for Computational Linguistics.
Cite (Informal):
Detecting Greenwashing in ESG Reports: A Comparative Analysis of Machine Learning Methods in Traffic-Related Emissions Disclosure (Florstedt et al., SwissText 2025)
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PDF:
https://aclanthology.org/2025.swisstext-1.3.pdf