37.118, Confs: 2nd Workshop on Ecology, Environment, and Natural Language Processing (Spain)

[The LINGUIST List]

LINGUIST List: Vol-37-118. Mon Jan 12 2026. ISSN: 1069 - 4875.

Subject: 37.118, Confs: 2nd Workshop on Ecology, Environment, and Natural Language Processing (Spain)

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Date: 09-Jan-2026
From: Francesca Grasso [fr.grasso at unito.it]
Subject: 2nd Workshop on Ecology, Environment, and Natural Language Processing


2nd Workshop on Ecology, Environment, and Natural Language Processing
Short Title: NLP4Ecology2026
Theme: Advancing computational linguistics research for ecology,
environment, and sustainability.

Date: 12-May-2026 - 12-May-2026
Location: Palma, Mallorca, Spain
Contact: Francesca Grasso
Contact Email: fr.grasso at unito.it
Meeting URL: https://nlp4ecology2026.di.unito.it/

Linguistic Field(s): Applied Linguistics; Computational Linguistics;
Discourse Analysis; Language Documentation; Text/Corpus Linguistics

Submission Deadline: 27-Feb-2026

We invite submissions to the 2nd Workshop on Ecology, Environment, and
Natural Language Processing. We are particularly interested in
contributions that push the boundaries of linguistics and NLP research
in the context of ecological and environmental crisis and that foster
interdisciplinary collaboration.
The topics of interest include, but are not limited to:
- Sentiment, Argument, and Stance Analysis of Environmental Topics:
Evaluating public opinions, emotions, and stances on ecological issues
across social media, news outlets, and other media, including
environmental activism communication and AI–environment debates (e.g.,
Longo and Longo, 2025; Ibrohim et al., 2023; Barz et al., 2025; Grasso
et al., 2024).
- Automated Linguistic and Discourse/Frame Analysis, and Topic
Modeling:
Studying grammatical, lexical, and discourse patterns in ecological
communication from an ecolinguistic perspective, including topic
modeling and framing analyses of media, political discourse, corporate
reports, and NGO communication (e.g., Widanti, 2022; Dehler-Holland et
al., 2021; Bosco et al., 2025; Grasso et al., 2025b).
- Detection of Anthropocentric and Speciesist Biases:
Identifying and mitigating anthropocentric and speciesist biases in
language data and NLP applications, including bias in large language
models (e.g., Leach et al., 2021; Takeshita et al., 2022; Grasso et
al., 2025a).
- Text Classification, Entity Recognition, and Environmental
Monitoring:
Categorizing texts into environmental subdomains such as biodiversity,
climate change, and conservation, and identifying or tracking mentions
of species, habitats, pollutants, and ecological phenomena, including
applications of LLMs to ecological and biodiversity corpora (e.g.,
Volkanovska, 2025; Schimanski et al., 2023; Abdelmageed et al., 2022;
Grasso & Locci, 2024).
- Fact-checking and Greenwashing Detection:
Analyzing corporate sustainability reports and institutional
communication to detect misleading claims, greenwashing practices, and
inaccuracies in environmental discourse (e.g., Glazkova and Zakharova,
2025; Cojoianu et al., 2020; Moodaley & Telukdarie, 2023).
- Ecofeminism, Environmental Justice, and Language:
Exploring the intersections of gender, justice, power, and ecological
narratives, and how NLP methods can support the analysis of
environmental justice–oriented discourse.
Further topics include:
 - Ecolinguistic applications of NLP.
 - Large Language Models (LLMs) application in Climate Change and
Environmental domain.
 - Analysis of harmful environmental narratives and misinformation on
social media.
 - Corpora creation and annotation for ecological discourse
 - Geo-tagging and Sentiment Mapping of Environmental Discussions
 - Fairness, ethics, and accountability in environmental NLP.
 - Environmental communication in low-resource languages.
 - Multimodal analysis for ecological and environmental challenges.
 - Lexical and semantic analysis of sustainability discourse.
 - Linked Data and Knowledge Graphs on ecological topics.
 - Language diversity and inclusion in environmental narratives.
 - Cognitive models and ecological storytelling.
 - NLP for understanding indigenous knowledge in environmental
contexts.
 - Machine learning techniques for analyzing environmental
communication.
 - NLP for environmental legislation and policy discourse.
 - NLP for environmental education and awareness campaigns.
 - Speech technologies to support ecological field research.
 - Educational chatbots and conversational agents for raising
environmental awareness.
We invite submissions in the following categories:
 - Regular Papers (from a minimum of 4 up to 8 pages)
 - Non-archival contributions (up to 4 pages).
 - Regular papers must report original, previously unpublished work
and follow the LREC 2026 Author Kit. Accepted regular papers will be
included in the workshop proceedings.
 - Non-archival contributions include research communications (i.e.
work already published at other venues), work in progress, manifestos,
and similar contributions. Non-archival contributions can be presented
at the workshop but will not be included in the proceedings.



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