@inproceedings{peura-etal-2025-perspectives,
    title = "Perspectives on Forests and Forestry in {Finnish} Online Discussions - A Topic Modeling Approach to Suomi24",
    author = "Peura, Telma  and
      Krizs{\'a}n, Attila  and
      Kuusalu, Salla-Riikka  and
      Laippala, Veronika",
    editor = "Basile, Valerio  and
      Bosco, Cristina  and
      Grasso, Francesca  and
      Ibrohim, Muhammad Okky  and
      Skeppstedt, Maria  and
      Stede, Manfred",
    booktitle = "Proceedings of the 1st Workshop on Ecology, Environment, and Natural Language Processing (NLP4Ecology2025)",
    month = mar,
    year = "2025",
    address = "Tallinn, Estonia",
    publisher = "University of Tartu Library",
    url = "https://preview.aclanthology.org/landing_page/2025.nlp4ecology-1.5/",
    pages = "10--15",
    ISBN = "978-9908-53-114-4",
    abstract = "This paper explores how forests and forest industry are perceived on the largest online discussion forum in Finland, Suomi24 ({\textquoteleft}Finland24'). Using 30,636 posts published in 2014{--}2020, we investigate what kind of topics and perspectives towards forest management can be found. We use BERTopic as our topic modeling approach and evaluate the results of its different modular combinations. As the dataset is not labeled, we demonstrate the validity of our best model through illustrating some of the topics about forest use. The results show that a combination of UMAP and K-means leads to the best topic quality. Our exploratory qualitative analysis indicates that the posts reflect polarized discourses between the forest industry and forest conservation adherents."
}