How does Facebook's automated detection system handle ads in multiple languages?

Facebook's automated detection system is capable of handling ads in multiple languages, using machine learning algorithms to analyze and evaluate the content of each ad.

When an ad is submitted in multiple languages, the system uses natural language processing (NLP) techniques to identify the language(s) used in the ad. It then analyzes the content of the ad in each language, taking into account factors such as the context, tone, and potential policy violations.

The system is designed to be language-agnostic, meaning that it can evaluate ads in any language, regardless of whether it has been trained on that specific language. However, the accuracy of the review may vary depending on the language and the complexity of the ad content.

To ensure the highest level of accuracy, Facebook may also use human reviewers who are fluent in the language(s) used in the ad. These reviewers can provide additional context and insight into the content of the ad, helping to ensure that it complies with Facebook's policies.

Overall, Facebook's automated detection system is designed to be flexible and adaptable, allowing it to handle ads in multiple languages while minimizing false positives and ensuring compliance with the platform's policies.