Designing Word Filter Tools for Creator-led Comment Moderation

TL;DR

This paper introduces FilterBuddy, a tool designed to help content creators craft, organize, and visualize comment filters more effectively, addressing challenges in moderation and audience understanding.

Contribution

The paper presents FilterBuddy, a novel system that supports creators in authoring, organizing, and visualizing comment filters to improve moderation and audience insights.

Findings

Creators struggle with writing and organizing filters.

FilterBuddy helps creators understand comment capture over time.

Participants view FilterBuddy as both a moderation and audience analysis tool.

Abstract

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.