Abstract
In this paper, we introduce a novel sociotechnical moderation system for Reddit called Crossmod. Through formative interviews with 11 active moderators from 10 different subreddits, we learned about the limitations of currently available automated tools, and how a new system could extend their capabilities. Developed out of these interviews, Crossmod makes its decisions based on cross-community learning—an approach that leverages a large corpus of previous moderator decisions via an ensemble of classifiers. Finally, we deployed Crossmod in a controlled environment, simulating real-time conversations from two large subreddits with over 10M subscribers each. To evaluate Crossmod’s moderation recommendations, 4 moderators reviewed comments scored by Crossmod that had been drawn randomly from existing threads. Crossmod achieved an overall accuracy of 86% when detecting comments that would be removed by moderators, with high recall (over 87.5%). Additionally, moderators reported that they would have removed 95.3% of the comments flagged by Crossmod; however, 98.3% of these comments were still online at the time of this writing (i.e., not removed by the current moderation system). To the best of our knowledge, Crossmod is the first open source, AI-backed sociotechnical moderation system to be designed using participatory methods.
Original language | English (US) |
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Article number | 174 |
Journal | Proceedings of the ACM on Human-Computer Interaction |
Volume | 3 |
Issue number | CSCW |
DOIs | |
State | Published - Nov 2019 |
Externally published | Yes |
Keywords
- AI
- Community norms
- Machine learning
- Mixed initiative
- Moderation
- Online communities
- Online governance
- Open source
- Participatory design
- Sociotechnical systems
ASJC Scopus subject areas
- Social Sciences (miscellaneous)
- Human-Computer Interaction
- Computer Networks and Communications