Abstract
Recent concerns over abusive behavior on their platforms have pressured social media companies to strengthen their content moderation policies. However, user opinions on these policies have been relatively understudied. In this paper, we present an analysis of user responses to a September 27, 2018 announcement about the quarantine policy on Reddit as a case study of to what extent the discourse on content moderation is polarized by users’ ideological viewpoint. We introduce a novel partitioning approach for characterizing user polarization based on their distribution of participation across interest subreddits. We then use automated techniques for capturing framing to examine how users with different viewpoints discuss moderation issues, finding that right-leaning users invoked censorship while left-leaning users highlighted inconsistencies on how content policies are applied. Overall, we argue for a more nuanced approach to moderation by highlighting the intersection of behavior and ideology in considering how abusive language is defined and regulated.- Anthology ID:
- W19-3507
- Volume:
- Proceedings of the Third Workshop on Abusive Language Online
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Sarah T. Roberts, Joel Tetreault, Vinodkumar Prabhakaran, Zeerak Waseem
- Venue:
- ALW
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 58–69
- Language:
- URL:
- https://aclanthology.org/W19-3507
- DOI:
- 10.18653/v1/W19-3507
- Cite (ACL):
- Qinlan Shen and Carolyn Rose. 2019. The Discourse of Online Content Moderation: Investigating Polarized User Responses to Changes in Reddit’s Quarantine Policy. In Proceedings of the Third Workshop on Abusive Language Online, pages 58–69, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- The Discourse of Online Content Moderation: Investigating Polarized User Responses to Changes in Reddit’s Quarantine Policy (Shen & Rose, ALW 2019)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/W19-3507.pdf
- Code
- qinlans/alw3_data