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ModSandbox: Facilitating Online Community Moderation Through Error Prediction and Improvement of Automated Rules
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dc.contributor.author Song, Jean Young -
dc.contributor.author Lee, Sangwook -
dc.contributor.author Lee, Jisoo -
dc.contributor.author Kim, Mina -
dc.contributor.author Kim, Juho -
dc.date.accessioned 2023-12-26T18:11:52Z -
dc.date.available 2023-12-26T18:11:52Z -
dc.date.created 2023-06-09 -
dc.date.issued 2023-04-26 -
dc.identifier.isbn 9781450394215 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/46770 -
dc.description.abstract Despite the common use of rule-based tools for online content moderation, human moderators still spend a lot of time monitoring them to ensure they work as intended. Based on surveys and interviews with Reddit moderators who use AutoModerator, we identified the main challenges in reducing false positives and false negatives of automated rules: not being able to estimate the actual effect of a rule in advance and having difficulty figuring out how the rules should be updated. To address these issues, we built ModSandbox, a novel virtual sandbox system that detects possible false positives and false negatives of a rule and visualizes which part of the rule is causing issues. We conducted a comparative, between-subject study with online content moderators to evaluate the effect of ModSandbox in improving automated rules. Results show that ModSandbox can support quickly finding possible false positives and false negatives of automated rules and guide moderators to improve them to reduce future errors. © 2023 ACM. -
dc.language English -
dc.publisher Association for Computing Machinery -
dc.title ModSandbox: Facilitating Online Community Moderation Through Error Prediction and Improvement of Automated Rules -
dc.type Conference Paper -
dc.identifier.doi 10.1145/3544548.3581057 -
dc.identifier.scopusid 2-s2.0-85160020586 -
dc.identifier.bibliographicCitation Song, Jean Young. (2023-04-26). ModSandbox: Facilitating Online Community Moderation Through Error Prediction and Improvement of Automated Rules. ACM Conference on Human Factors in Computing Systems, 1–20. doi: 10.1145/3544548.3581057 -
dc.identifier.url https://programs.sigchi.org/chi/2023/program/content/96598 -
dc.citation.conferencePlace GE -
dc.citation.conferencePlace Hamburg -
dc.citation.endPage 20 -
dc.citation.startPage 1 -
dc.citation.title ACM Conference on Human Factors in Computing Systems -
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송진영
Song, Jean Young송진영

Department of Electrical Engineering and Computer Science

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