# Content Moderation Justice and Fairness on Social Media: Comparisons Across Different Contexts and Platforms

arXiv: https://arxiv.org/abs/2403.06034 · HTML: https://mlsanity.com/paper/2403.06034/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Mar 2024.

## Built on by (most cited first, 4 of 4)

- [Lost in Moderation: How Commercial Content Moderation APIs Over- and Under-Moderate Group-Targeted Hate Speech and Linguistic Variations](https://mlsanity.com/paper/2503.01623/) (2025)
- [Silencing Empowerment, Allowing Bigotry: Auditing the Moderation of Hate Speech on Twitch](https://mlsanity.com/paper/2506.07667/) (2025)
- [How Generative AI Empowers Attackers and Defenders Across the Trust & Safety Landscape](https://mlsanity.com/paper/2601.06033/) (2025)
- [To Lie or Not to Lie? Investigating The Biased Spread of Global Lies by LLMs](https://mlsanity.com/paper/2604.06552/) (2026)

## Abstract (arXiv)

Social media users may perceive moderation decisions by the platform differently, which can lead to frustration and dropout. This study investigates users' perceived justice and fairness of online moderation decisions when they are exposed to various illegal versus legal scenarios, retributive versus restorative moderation strategies, and user-moderated versus commercially moderated platforms. We conduct an online experiment on 200 American social media users of Reddit and Twitter. Results show that retributive moderation delivers higher justice and fairness for commercially moderated than for user-moderated platforms in illegal violations; restorative moderation delivers higher fairness for legal violations than illegal ones. We discuss the opportunities for platform policymaking to improve moderation system design.