Help:New filters for edit review/it

Nuovi filtri per la revisione delle modifiche è una funzionalità sperimentale che aggiunge nuovi filtraggi e altri strumenti come un'interfaccia migliorata per il filtraggio a Speciale:UltimeModifiche e Speciale:ModificheCorrelate (inizialmente).

These tools help reviewers to better target their efforts and be more efficient. They also have the potential to particularly benefit new contributors, who require a more supportive edit-review process, according to research.

To learn about the parts of the improved user interface visit the quick tour. To learn how to use the advanced functions provided, explore the pages described below.

The roll out of this new feature starts in March 2017. The “New filters for edit review” beta is not initially available on mobile.

Funzioni principali

 * This page explains how the improved filtering interface works and how to get the most out of the new tools.
 * This page explains how the improved filtering interface works and how to get the most out of the new tools.


 * User-defined Highlighting tools let you use color to emphasize the edits that interest you most. The functions and techniques described on this page will help you to make your Recent Changes results more meaningful.
 * User-defined Highlighting tools let you use color to emphasize the edits that interest you most. The functions and techniques described on this page will help you to make your Recent Changes results more meaningful.


 * "New filters for edit review" introduces two filter groups—Contribution Quality and User Intent—that are powered by machine learning and work differently from other filters. They offer probabilistic predictions about, respectively, whether or not edits are likely to contain problems and whether the user who made them was acting in good faith. Knowing a bit about how these unique tools work will help you use them more effectively.
 * "New filters for edit review" introduces two filter groups—Contribution Quality and User Intent—that are powered by machine learning and work differently from other filters. They offer probabilistic predictions about, respectively, whether or not edits are likely to contain problems and whether the user who made them was acting in good faith. Knowing a bit about how these unique tools work will help you use them more effectively.


 * Save and restore your favorite filters.
 * Save and restore your favorite filters.


 * Filtered results are updated periodically.
 * Filtered results are updated periodically.

Vedi anche

 * Domande più frequenti
 * Domande più frequenti


 * Ongoing discussions and feedback provided by users.
 * Ongoing discussions and feedback provided by users.

Other resources

 * Powerful new search tools help edit patrollers find their targets, blogpost by Joe Matazzoni