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Detecting Perspective-Getting in Wikipedia Discussions

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

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.

Original languageEnglish
Title of host publicationProceedings of the Sixth Workshop on Natural Language Processing and Computational Social Science (NLP+CSS 2024)
EditorsDallas Card, Anjalie Field, Dirk Hovy, Katherine Keith
PublisherAssociation for Computational Linguistics (ACL)
Pages1-15
Number of pages15
ISBN (Electronic)9798891761124
DOIs
Publication statusPublished - 2024
Event6thWorkshop on Natural Language Processing and Computational Social Science, NLP+CSS 2024 - Mexico City, Mexico
Duration: 21 Jun 2024 → …

Conference

Conference6thWorkshop on Natural Language Processing and Computational Social Science, NLP+CSS 2024
Country/TerritoryMexico
CityMexico City
Period21/06/24 → …

Bibliographical note

Publisher Copyright:
© 2024 Association for Computational Linguistics.

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