Take the Power Back: Screen-Based Personal Moderation Against Hate Speech on Instagram

TL;DR

This study investigates user preferences for personal moderation tools on Instagram to combat hate speech, highlighting prioritized screens and desired features through a Delphi study with activists.

Contribution

It provides insights into user preferences for personal moderation features and screens on Instagram, informing user-centered design to improve hate speech mitigation.

Findings

Users prioritize moderation on comments and reels screens.

Features for reversibility and oversight are highly valued.

Automated, content-specific features are less universally preferred.

Abstract

Hate speech remains a pressing challenge on social media, where platform moderation often fails to protect targeted users. Personal moderation tools that let users decide how content is filtered can address some of these shortcomings. However, it remains an open question on which screens (e.g., the comments, the reels tab, or the home feed) users want personal moderation and which features they value most. To address these gaps, we conducted a three-wave Delphi study with 40 activists who experienced hate speech. We combined quantitative ratings and rankings with open questions about required features. Participants prioritized personal moderation for conversational and algorithmically curated screens. They valued features allowing for reversibility and oversight across screens, while input-based, content-type specific, and highly automated features are more screen specific. We discuss the importance of personal moderation and offer user-centered design recommendations for personal moderation on Instagram.