@inproceedings{bassi-etal-2025-old,
    title = "Old but Gold: {LLM}-Based Features and Shallow Learning Methods for Fine-Grained Controversy Analysis in {Y}ou{T}ube Comments",
    author = "Bassi, Davide  and
      Marino, Erik Bran  and
      Vieira, Renata  and
      Pereira, Martin",
    editor = "Chistova, Elena  and
      Cimiano, Philipp  and
      Haddadan, Shohreh  and
      Lapesa, Gabriella  and
      Ruiz-Dolz, Ramon",
    booktitle = "Proceedings of the 12th Argument mining Workshop",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/landing_page/2025.argmining-1.5/",
    pages = "46--57",
    ISBN = "979-8-89176-258-9",
    abstract = "Online discussions can either bridge differences through constructive dialogue or amplify divisions through destructive interactions. paper proposes a computational approach to analyze dialogical relation patterns in YouTube comments, offering a fine-grained framework for controversy detection, enabling also analysis of individual contributions. experiments demonstrate that shallow learning methods, when equipped with these theoretically-grounded features, consistently outperform more complex language models in characterizing discourse quality at both comment-pair and conversation-chain levels.studies confirm that divisive rhetorical techniques serve as strong predictors of destructive communication patterns. work advances understanding of how communicative choices shape online discourse, moving beyond engagement metrics toward nuanced examination of constructive versus destructive dialogue patterns."
}