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Computer Science > Computation and Language

arXiv:2405.08142 (cs)
[Submitted on 13 May 2024]

Title:Discursive objection strategies in online comments: Developing a classification schema and validating its training

Authors:Ashley L. Shea, Aspen K.B. Omapang, Ji Yong Cho, Miryam Y. Ginsparg, Natalie Bazarova, Winice Hui, René F. Kizilcec, Chau Tong, Drew Margolin
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Abstract:Most Americans agree that misinformation, hate speech and harassment are harmful and inadequately curbed on social media through current moderation practices. In this paper, we aim to understand the discursive strategies employed by people in response to harmful speech in news comments. We conducted a content analysis of more than 6500 comment replies to trending news videos on YouTube and Twitter and identified seven distinct discursive objection strategies (Study 1). We examined the frequency of each strategy's occurrence from the 6500 comment replies, as well as from a second sample of 2004 replies (Study 2). Together, these studies show that people deploy a diversity of discursive strategies when objecting to speech, and reputational attacks are the most common. The resulting classification scheme accounts for different theoretical approaches for expressing objections and offers a comprehensive perspective on grassroots efforts aimed at stopping offensive or problematic speech on campus.
Comments: This paper was accepted and presented at the 73rd Annual International Communication Association International Conference, May 2023
Subjects: Computation and Language (cs.CL); Computers and Society (cs.CY)
ACM classes: I.2.7, J.4
Cite as: arXiv:2405.08142 [cs.CL]
  (or arXiv:2405.08142v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2405.08142

Submission history

From: Ashley Shea [view email]
[v1] Mon, 13 May 2024 19:39:00 UTC (441 KB)
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