Bans vs. Warning Labels: Examining Bystanders' Support for Community-wide Moderation Interventions

TL;DR

This study investigates how bystanders perceive community-wide moderation interventions like bans and warning labels on social media, revealing that perceived effects on others and free speech beliefs influence support, with bans seen as too coarse and moderation tailored to infractions valued.

Contribution

It provides empirical insights into user perceptions of community sanctions, highlighting factors influencing support for bans versus warning labels in online communities.

Findings

Perceived effects on others predict support for both interventions.

Free speech beliefs influence support for warning labels.

Bans are viewed as too coarse and less favored by users.

Abstract

Social media platforms like Facebook and Reddit host thousands of user-governed online communities. These platforms sanction communities that frequently violate platform policies; however, public perceptions of such sanctions remain unclear. In a pre-registered survey conducted in the US, I explore bystander perceptions of content moderation for communities that frequently feature hate speech, violent content, and sexually explicit content. Two community-wide moderation interventions are tested: (1) community bans, where all community posts are removed, and (2) community warning labels, where an interstitial warning label precedes access. I examine how third-person effects and support for free speech influence user approval of these interventions on any platform. My regression analyses show that presumed effects on others are a significant predictor of backing for both interventions, while free speech beliefs significantly influence participants' inclination for using warning labels. Analyzing the open-ended responses, I find that community-wide bans are often perceived as too coarse, and users instead value sanctions in proportion to the severity and type of infractions. I report on concerns that norm-violating communities could reinforce inappropriate behaviors and show how users' choice of sanctions is influenced by their perceived effectiveness. I discuss the implications of these results for HCI research on online harms and content moderation.