TY - GEN
T1 - Designing Word Filter Tools for Creator-led Comment Moderation
AU - Jhaver, Shagun
AU - Chen, Quan Ze
AU - Knauss, Detlef
AU - Zhang, Amy X.
N1 - Publisher Copyright:
© 2022 ACM.
PY - 2022/4/29
Y1 - 2022/4/29
N2 - Online social platforms centered around content creators often allow comments on content, where creators can then 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 revising 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 pre-made ones, as well as organizing their filters and visualizing what comments are captured by them 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.
AB - Online social platforms centered around content creators often allow comments on content, where creators can then 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 revising 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 pre-made ones, as well as organizing their filters and visualizing what comments are captured by them 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.
KW - FilterBuddy
KW - YouTube
KW - content creators
KW - content moderation
KW - human-computer integration
KW - online harassment
KW - platform governance
UR - http://www.scopus.com/inward/record.url?scp=85130549850&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85130549850&partnerID=8YFLogxK
U2 - 10.1145/3491102.3517505
DO - 10.1145/3491102.3517505
M3 - Conference contribution
AN - SCOPUS:85130549850
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2022 - Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
T2 - 2022 CHI Conference on Human Factors in Computing Systems, CHI 2022
Y2 - 30 April 2022 through 5 May 2022
ER -