  Online social platforms centered around content creators often allow comments
on content, where creators moderate the comments they receive. As creators can
face overwhelming numbers of comments, with some of them harassing or hateful,
platforms typically provide tools such as word filters for creators to automate
aspects of moderation. From needfinding interviews with 19 creators about how
they use existing tools, we found that they struggled with writing good filters
as well as organizing and revisiting their filters, due to the difficulty of
determining what the filters actually catch. To address these issues, we
present FilterBuddy, a system that supports creators in authoring new filters
or building from existing filter lists, as well as organizing their filters and
visualizing what comments are captured over time. We conducted an early-stage
evaluation of FilterBuddy with YouTube creators, finding that participants see
FilterBuddy not just as a moderation tool, but also a means to organize their
comments to better understand their audiences.
