Machine Learning Model: Language agnostic revert risk

User story & summary:

As a patroller, I want to filter Recent Changes by revert risk, so that I have the filters I need to effectively patrol recent edits.

Background & research:

Patrolling content in more than 250+ Wikipedia projects is a difficult task. The amount of revisions, plus the different languages involved requires a complex human effort. The aim of this model is to help patrollers quickly identify potential problems, and revert damaging edits when needed.

Previous models had tried to solve this by creating language-specific solutions, however, that approach is difficult to escalate and maintain, because it requires as many models as languages used on the Wikimedia projects. Moreover, complex-language models are just available in certain languages, leaving out smaller Wikipedia editions. Therefore, this model is based on Language Agnostic features, making it possible to use it for any existing Wikipedia, and for new language projects that can appear in the future.

Learn more about the model here: https://meta.wikimedia.org/wiki/Machine_learning_models/Proposed/Language-agnostic_revert_risk

Acceptance Criteria:

• Partner with Growth, Android and Moderator Tools Product Managers on a release plan
• Draft communication plan