AppealMod: Inducing Friction to Reduce Moderator Workload of Handling User Appeals
Shubham Atreja, Jane Im, Paul Resnick, Libby Hemphill

TL;DR
AppealMod introduces a friction-based system for handling user appeals on social media, reducing moderator workload and exposure to toxic content by encouraging users to provide more information upfront.
Contribution
The paper presents AppealMod, a novel system that induces friction in the appeal process to filter insincere and toxic appeals, supported by a large-scale field experiment.
Findings
Reduced appeals viewed by moderators to 30%
Less than 10% of toxic appeals reached moderators
Maintained appeal approval rates despite filtering
Abstract
As content moderation becomes a central aspect of all social media platforms and online communities, interest has grown in how to make moderation decisions contestable. On social media platforms where individual communities moderate their own activities, the responsibility to address user appeals falls on volunteers from within the community. While there is a growing body of work devoted to understanding and supporting the volunteer moderators' workload, little is known about their practice of handling user appeals. Through a collaborative and iterative design process with Reddit moderators, we found that moderators spend considerable effort in investigating user ban appeals and desired to directly engage with users and retain their agency over each decision. To fulfill their needs, we designed and built AppealMod, a system that induces friction in the appeals process by asking users to…
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Taxonomy
TopicsHate Speech and Cyberbullying Detection · Software Engineering Research · Advanced Malware Detection Techniques
