Analyzing the Online Communication of Environmental Movement Organizations: NLP Approaches to Topics, Sentiment, and Emotions

Christina Barz, Melanie Siegel, Daniel Hanss


Abstract
This project employs state-of-the-art Natural Language Processing (NLP) techniques to analyze the online communication of international Environmental Movement Organizations (EMOs). First, we introduce our overall EMO dataset and describe it through topic modeling. Second, we evaluate current sentiment and emotion classification models for our specific dataset. Third, as we are currently in our annotation process, we evaluate our current progress and issues to determine the most effective approach for creating a high-quality annotated dataset that captures the nuances of EMO communication. Finally, we emphasize the need for domain-specific datasets and tailored NLP tools and suggest refinements for our annotation process moving forward.
Anthology ID:
2025.nlp4ecology-1.15
Volume:
Proceedings of the 1st Workshop on Ecology, Environment, and Natural Language Processing (NLP4Ecology2025)
Month:
march
Year:
2025
Address:
Tallinn, Estonia
Editors:
Valerio Basile, Cristina Bosco, Francesca Grasso, Muhammad Okky Ibrohim, Maria Skeppstedt, Manfred Stede
Venues:
NLP4Ecology | WS
SIG:
Publisher:
University of Tartu Library
Note:
Pages:
68–76
Language:
URL:
https://preview.aclanthology.org/fix-sig-urls/2025.nlp4ecology-1.15/
DOI:
Bibkey:
Cite (ACL):
Christina Barz, Melanie Siegel, and Daniel Hanss. 2025. Analyzing the Online Communication of Environmental Movement Organizations: NLP Approaches to Topics, Sentiment, and Emotions. In Proceedings of the 1st Workshop on Ecology, Environment, and Natural Language Processing (NLP4Ecology2025), pages 68–76, Tallinn, Estonia. University of Tartu Library.
Cite (Informal):
Analyzing the Online Communication of Environmental Movement Organizations: NLP Approaches to Topics, Sentiment, and Emotions (Barz et al., NLP4Ecology 2025)
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PDF:
https://preview.aclanthology.org/fix-sig-urls/2025.nlp4ecology-1.15.pdf