Edit Review Improvements/New filters for edit review/es

La página Especial:Cambios Recientes es el punto de partida para muchos tipos de revisión de ediciones. El equipo de Colaboración está planificando el desarrollo de un nuevo conjunto de herramientas —inicialmente como opción beta— diseñado para mejorar la revisión de ediciones en la página CR. Si tiene éxito, es probable que estas mejoras se extiendan a la lista de seguimiento y a otras páginas de revisión.

Entre las nuevas herramientas y mejoras, cabe destacar un conjunto de filtros predictivos basados en el programa de aprendizaje automático ORES y una nueva interfaz que mejora tanto la experiencia de usuario como la eficacia de las búsquedas.

Estas funcionalidades ayudarán a los revisores en general a enfocar mejor sus esfuerzos y ser más eficientes. Las mejoras también tienen el potencial de beneficiar en particular a los colaboradores nuevos, que requieren de un mayor apoyo en la revisión de sus ediciones, de acuerdo con los estudios. Para ello, se valdrán de la inteligencia artificial para detectar ediciones de colaboradores que a) sean nuevos y b) cometan errores, pero c) de buena fe (un objetivo claro de las mejoras en la revisión de ediciones).

Estos cambios también afectarán a Especial:CambiosEnEnlazadas. Descubre esta nueva funcionalidad en la página de Visita Rápida.

Mejoras en la Fase 1


Los cambios de la Fase 1 en la página CR (que estarán concluidos previsiblemente para marzo de 2017) incluyen las siguientes funcionalidades y mejoras:

Predicciones de calidad de las contribuciones
By enabling users to filter for good-quality edits, these filters empower reviewers who are, for example, looking to thank contributors; by helping detect bad-quality edits, they make numerous types of edit-review more efficient. The quality predictions are made by ORES, a machine learning service trained on a large set of edits previously scored by human editors.

Filters with different levels of accuracy are provided (ranging from "Very likely have problems" to "May have problems"). Stricter, more accurate filters find fewer false positives but return fewer results overall and so miss more of their target. Less accurate filters cast a wider net and find more of their target, but they also find proportionally more false positives. Learn more about predictions.

User intent predictions
By enabling users to filter for edits made in good-faith, these filters empower reviewers seeking to support good-faith users; by enabling detection of bad-faith edits, they assist reviewers looking for vandalism. Like the Quality filters above, these predictions are made by the machine-learning service ORES. Also as above, filters at different levels of accuracy are provided to meet different users' needs. Learn more about predictions.

Experience level filters
Research shows that new editors are particularly vulnerable to rejection. The Experience level filters enable reviewers to treat new users with the care they require and to identify contributions by users at a couple of more advanced levels. These are the Experience level filters:


 * Newcomer: fewer than 10 edits and 4 days of activity
 * Learners: more days of activity and edits than “Newcomers” but fewer than “Experienced users.” (corresponds to autoconfirmed status)
 * Experienced users: more than 30 days of activity and 500 edits. (corresponds to extended confirmed status)

The filters return the edits only of users who are currently logged in.

Aprende más sobre filtrados.

Filtrado más potente
Most previous RC page filters offered only a simple option to show or hide a certain property (X). By augmenting these filters so that they now let users show or hide both X and its opposite (notX), the current tools provide more control. For example, previously, one could show Wikidata edits or hide Wikidata edits, but one could not show only Wikidata edits.

Furthermore, by organizing filters into logical groups, the new arrangement provides an improved ability to narrow results. (Logically, the new arrangement provides groups of OR filters, with each group of ORs being connected to other groups by ANDs.) Aprende más sobre filtrado.

Highlighting function
Among the many user interface improvements included in this project is a user-controllable highlighting function. By letting reviewers apply color to emphasize desired edit properties in the results area, Highlighting makes Recent Changes search results more meaningful. Among other user benefits, this new interpretive layer adds another tool for prioritizing work. Learn more about highlighting functions.

Beyond Phase One
Once the Beta features described above are in place, we will gather user input and test satisfaction, then finalize plans for more improvements. The following options are under consideration:

Extend new functionality to more pages
Add the new filters and improved filtering interface to Watchlist, User contributions, Related changes and other, similar pages.

“Recently used filters”
By enabling the system to remember reviewers’ recent filter settings, help users to repeat their most common tasks quickly and easily, without having to input settings each time.

Upgrade interface and capabilities for the untouched RC page features
Phase one changes won’t affect all tools on the RC page. The following tools will remain unchanged: Namespace filters, Tag filters, filters for time frame, and number of results. Future efforts will likely bring these tools up to the new UI standard. This will enable the selection of multiple namespaces, multiple tag filters, and more specific time-frames.

Support ORES for propagated Wikidata edits
ORES supports Wikidata. You can enable it on wikidata.org and use it on Wikidata' Special:RecentChanges. The ORES extension doesn't currently handle these edits on the client-side (e.g. when viewing Wikidata changes relevant to any Wikipedia in Wikipedia RecentChanges page). We plan to fix it.