@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",
doi = "10.18653/v1/2024.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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Detecting Perspective-Getting in Wikipedia Discussions
%A Vasilets, Evgeny
%A Broek, Tijs
%A Wegmann, Anna
%A Abadi, David
%A Nguyen, Dong
%Y Card, Dallas
%Y Field, Anjalie
%Y Hovy, Dirk
%Y Keith, Katherine
%S Proceedings of the Sixth Workshop on Natural Language Processing and Computational Social Science (NLP+CSS 2024)
%D 2024
%8 June
%I Association for Computational Linguistics
%C Mexico City, Mexico
%F vasilets-etal-2024-detecting
%X 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.
%R 10.18653/v1/2024.nlpcss-1.1
%U https://aclanthology.org/2024.nlpcss-1.1
%U https://doi.org/10.18653/v1/2024.nlpcss-1.1
%P 1-15
Markdown (Informal)
[Detecting Perspective-Getting in Wikipedia Discussions](https://aclanthology.org/2024.nlpcss-1.1) (Vasilets et al., NLP+CSS-WS 2024)
ACL
- Evgeny Vasilets, Tijs Broek, Anna Wegmann, David Abadi, and Dong Nguyen. 2024. Detecting Perspective-Getting in Wikipedia Discussions. In Proceedings of the Sixth Workshop on Natural Language Processing and Computational Social Science (NLP+CSS 2024), pages 1–15, Mexico City, Mexico. Association for Computational Linguistics.