Personalizing Content Moderation on Social Media: User Perspectives on Moderation Choices, Interface Design, and Labor

Author:

Jhaver Shagun1ORCID,Zhang Alice Qian2ORCID,Chen Quan Ze3ORCID,Natarajan Nikhila1ORCID,Wang Ruotong4ORCID,Zhang Amy X.3ORCID

Affiliation:

1. Rutgers University, New Brunswick, NJ, USA

2. University of Minnesota, Minneapolis, MN, USA

3. University of Washington, Seattle, WA, USA

4. University of Washington, Seattle , WA, USA

Abstract

Social media platforms moderate content for each user by incorporating the outputs of both platform-wide content moderation systems and, in some cases, user-configured personal moderation preferences. However, it is unclear (1) how end users perceive the choices and affordances of different kinds of personal content moderation tools, and (2) how the introduction of personalization impacts user perceptions of platforms' content moderation responsibilities. This paper investigates end users' perspectives on personal content moderation tools by conducting an interview study with a diverse sample of 24 active social media users. We probe interviewees' preferences using simulated personal moderation interfaces, including word filters, sliders for toxicity levels, and boolean toxicity toggles. We also examine the labor involved for users in choosing moderation settings and present users' attitudes about the roles and responsibilities of social media platforms and other stakeholders toward moderation. We discuss how our findings can inform design solutions to improve transparency and controllability in personal content moderation tools.

Funder

Google

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications,Human-Computer Interaction,Social Sciences (miscellaneous)

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5. Moodplay

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