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.