Our Approach To Dangerous Organizations and Individuals
How we approach dangerous organizations and individuals.
Our approach to the opioid epidemic
How we support communities in the face of the opioid epidemic.
Our approach to elections
How we help prevent interference, empower people to vote and more.
Our approach to misinformation
How we work with independent fact-checkers, and more, to identify and take action on misinformation.
Our approach to newsworthy content
How we assess content for newsworthiness.
Our approach to Facebook Feed ranking
How we reduce problematic content in News Feed.
Our approach to explaining ranking
How we build AI systems.
Content Library and Content Library API
Comprehensive access to public data from Facebook and Instagram
Ad Library tools
Comprehensive and searchable database of all ads currently running across Meta technologies
Other research tools and datasets
Additional tools for in-depth research on Meta technologies and programs
Community Standards Enforcement Report
Quarterly report on how well we're doing at enforcing our policies on the Facebook app and Instagram.
Intellectual Property
Report on how well we're helping people protect their intellectual property.
Government Requests for User Data
Report on government request for people's data.
Content Restrictions Based on Local Law
Report on when we restrict content that's reported to us as violating local law.
Internet Disruptions
Report on intentional internet restrictions that limit people's ability to access the internet.
Widely Viewed Content Report
Quarterly report on what people see on Facebook, including the content that receives the widest distribution during the quarter.
Regulatory and Other Transparency Reports
Download current and past regulatory reports for Facebook and Instagram.
Meta often receives questions about how our content review process works, how we enforce our policies and whether our review teams apply our policies globally. Here’s what our review teams do and how they use our technology to do their work.
Content review: when we use technology and when we use human review
When something goes against the Community Standards, Meta has content enforcement systems in place to respond. For example, we use artificial intelligence and machine learning tools to help us identify and remove a large amount of violating content—often, before anyone sees it.
In those instances where our technology misses something or needs more input, we rely on thousands of reviewers around the world to enforce our Community Standards.
As potential content violations get routed to review teams, each reviewer is assigned a queue of posts to individually evaluate. Sometimes, this review means simply looking at a post to determine whether it goes against our policies, such as an image containing adult nudity, in instances when our technology didn’t detect it first.
In other cases, context is key. For example, our technology might be unsure whether a post contains bullying, a policy area that requires extra context and nuance because it often reflects the nature of personal relationships. In this case, we’ll send the post to review teams that have the right subject matter and language expertise for further review. If necessary, they can also escalate it to subject matter experts on the Global Operations or Content Policy teams.
When necessary, we also provide reviewers additional information from the reported content. For example, words that are historically used as racial slurs might be used as hate speech by one person but can also be a form of self-empowerment when shared by another person, in a different context. In some cases, we may provide additional context about such words to reviewers to help them apply our policies and decide whether the post should be left up or taken down.
How technology detects violations