@inproceedings{vasilets-etal-2024-detecting,
    title = "Detecting Perspective-Getting in {W}ikipedia Discussions",
    author = "Vasilets, Evgeny  and
      Broek, Tijs  and
      Wegmann, Anna  and
      Abadi, David  and
      Nguyen, Dong",
    editor = "Card, Dallas  and
      Field, Anjalie  and
      Hovy, Dirk  and
      Keith, Katherine",
    booktitle = "Proceedings of the Sixth Workshop on Natural Language Processing and Computational Social Science (NLP+CSS 2024)",
    month = jun,
    year = "2024",
    address = "Mexico City, Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.nlpcss-1.1",
    pages = "1--15",
    abstract = "Perspective-getting (i.e., the effort to obtain information about the other person{'}s perspective) can lead to more accurate interpersonal understanding. In this paper, we develop an approach to measure perspective-getting and apply it to English Wikipedia discussions. First, we develop a codebook based on perspective-getting theory to operationalize perspective-getting into two categories: asking questions about and attending the other{'}s perspective. Second, we use the codebook to annotate perspective-getting in Wikipedia discussion pages. Third, we fine-tune a RoBERTa model that achieves an average F-1 score of 0.76 on the two perspective-getting categories. Last, we test whether perspective-getting is associated with discussion outcomes. Perspective-getting was not higher in non-escalated discussions. However, discussions starting with a post attending the other{'}s perspective are followed by responses that are more likely to also attend the other{'}s perspective. Future research may use our model to study the influence of perspective-getting on the dynamics and outcomes of online discussions.",
}