How well do content moderation systems serve users outside dominant English-speaking contexts—especially those posting online or accessing services using indigenous and other widely-spoken languages?
Each of the four case studies surveyed social media users and interviewed Trust & Safety practitioners, content moderators, content creators, and digital rights advocates to examine how content policies are defined, enforced, and experienced in each region. We also explored the role of automated systems like natural language processing (NLP) and large language models (LLMs), and how these systems could be built given the low availability of digitized data in many of these languages.
Our findings reveal significant gaps in how platforms moderate across languages and regions—highlighting the need for more inclusive, transparent, and locally informed systems. The project produced five reports: one comparative analysis and four region-specific briefs. Each report is available in English and the relevant local language.
Our goal is to support more equitable content governance, inform future research, and ensure that content moderation better reflects the needs of diverse communities around the world.
“'These platforms were not made for us.' Many content creators and digital rights advocates expressed this sentiment as we interviewed them for a recent study evaluating how Tamil speakers experienced content moderation on social media.”
