AppealMod: Inducing Friction to Reduce Moderator Workload of Handling User Appeals
Proceedings of the ACM on Human-Computer Interaction(2023)
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 provide
additional information before their appeals are reviewed by human moderators.
In addition to giving moderators more information, we expected the friction in
the appeal process would lead to a selection effect among users, with many
insincere and toxic appeals being abandoned before getting any attention from
human moderators. To evaluate our system, we conducted a randomized field
experiment in a Reddit community of over 29 million users that lasted for four
months. As a result of the selection effect, moderators viewed only 30
initial appeals and less than 10
granted roughly the same number of appeals when compared with the control
group. Overall, our system is effective at reducing moderator workload and
minimizing their exposure to toxic content while honoring their preference for
direct engagement and agency in appeals.
MoreTranslated text
Key words
collaborative design,contestability,effort asymmetry,field experiment,friction,moderation tools,online content moderation,self-selection
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