8 citations · 10 across the 4 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
cs.CL2023★ 1 cited
How We Define Harm Impacts Data Annotations: Explaining How Annotators Distinguish Hateful, Offensive, and Toxic Comments
Angela Schöpke-Gonzalez, Siqi Wu, Sagar Kumar +2
Computational social science research has made advances in machine learning and natural language processing that support content moderators in detecting harmful content. These adva…
cs.CY2023★ 8 cited
AppealMod: Inducing Friction to Reduce Moderator Workload of Handling User Appeals
Shubham Atreja, Jane Im, Paul Resnick +1
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 m…