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Not Everything Is Greenwashing: Limitations of Automatic Analysis of Sustainability Reports, and a Proposal

Paper · 2026 · Maria Pilar Uribe Silva, Rik van Noord and Malvina Nissim

Summary

Companies are legally required to publish sustainability reports (SRs), and most large firms do. However, these reports follow no standard format and often use deliberately vague wording, so it is hard to tell whether their claims are sincere. This position paper argues that NLP research on SRs has been too narrow. It mostly targets climate-related claims and "greenwashing," a label that is both fuzzy and overly restrictive, and it focuses on what statements say rather than how they are phrased.

The authors survey three research strands: manual discourse analysis, classic NLP and text-mining pipelines, and LLM-based systems. LLMs catch explicit claims at scale but miss subtle tactics such as selective disclosure or aspirational rhetoric, and they show a truth bias. Using excerpts from H&M's 2023 report, the authors show that a statement can be deceptive without counting as greenwashing under the EU Green Claims Directive Proposal. Even factually true sentences can mislead. They call for a transdisciplinary framework grounded in deception theory and corporate communication research, and they list open challenges.

Key points

  • A KPMG 2024 survey cited in the paper finds that 96% of the world's 250 largest companies publish SRs. No mandated format or shared vocabulary exists, despite frameworks such as GRI, SASB, and the UN SDGs.
  • A review by Calamai et al. (2026) covering 61 studies found no dataset explicitly labelled for greenwashing. Most work splits the problem into proxy tasks such as climate-claim detection and tone analysis.
  • The paper discusses these existing tools and systems: ClimateQA, ESGReveal (LLM + RAG), DocQA, LLM-built knowledge graphs, and GRI-oriented extraction pipelines.
  • Table 1 collects passages from H&M's 2023 sustainability report that the authors classify as deceptive. Not all of them meet the EU Green Claims Directive Proposal's definition of greenwashing.
  • The paper gives an example of a misleading true claim: a reported 20% emissions cut may result from a temporary facility closure while long-term emissions keep rising.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Institutions

🎓University of GroningenGroningen · Netherlands74 works · 5,142 citations

 Fields, topics and concepts

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Business, Management and Accounting · 40 worksMarketing · 4 worksAccounting · 5 worksStrategy and Management · 4 works

Cite

Cite as Maria Pilar Uribe Silva, Rik van Noord and Malvina Nissim. 2026. Not Everything Is Greenwashing: Limitations of Automatic Analysis of Sustainability Reports, and a Proposal. Proceedings of the 2nd Workshop on Ecology, Environment, and Natural Language Processing.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.63317/2jfjim27sf47

@inproceedings{silva2026not,
  title = {{Not Everything Is Greenwashing: Limitations of Automatic Analysis of Sustainability Reports, and a Proposal}},
  author = {Maria Pilar Uribe Silva, Rik {van Noord} and Malvina Nissim},
  booktitle = {Proceedings of the 2nd Workshop on Ecology, Environment, and Natural Language Processing},
  year = {2026},
  doi = {10.63317/2jfjim27sf47},
  url = {https://doi.org/10.63317/2jfjim27sf47}
}

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