Help:New filters for edit review/Glossary

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The following terms are relevant to the Edit Review Improvements project (ERI). Terms in italics are entries of that glossary.

ERI components and special terms

Edit Review Improvements: Also known as ERI; Edit Review Improvements (ERI) is a project of the Collaboration Team that is seeks to reduce the negative effects current edit-review processes can have on new editors to the wikis—while improving edit-review processes overall.
New filters for edit review: Also known as Filters for Special:Recent Changes.; One of the first product releases of the Edit Review Improvements project is a suite of improvements to the Recent Changes special page that are designed to help reviewers in general to better target their efforts and be more efficient. The improvements also have the potential to particularly benefit new contributors.
ReviewStream: ReviewStream is a machine-readable feed that’s designed to be used by a variety of edit-review tools. Like RCStream, it will broadcast recent changes from MediaWiki wikis. To the information currently in RCStream, ReviewStream adds additional data designed to improve the edit-review process.
Filter search bar: Part of the Recent Changes Page Improvements. Users click in the Filter Search Bar to begin the process of filtering recent changes, either by clicking to select filters from the Dropdown Filter Panel (see below) or by typing their names.
Dropdown Filter Panel: Part of the Recent Changes Page Improvements. The filter panel is a dropdown menu that displays a list of filtering options.
Active Filter Display Area: Part of the Recent Changes Page Improvements. The active filter display area is designed to give users a quick read of their current filter and highlighting settings.
Newcomers: A new user class defined for ERI denoting registered editors who are very new, having fewer than ten edits and four days of activity. Created because research shows that such editors are particularly vulnerable to rejections. Also the name of a filter in ERI projects.
Learners: A term defined for ERI denoting registered editors who have more days of activity and edits than “Newcomers” but fewer than “Experienced Users”. Also the name of a filter in ERI projects. On English Wikipedia, this category corresponds to Autoconfirmed.
Experienced Users: A term defined for ERI denoting registered editors who have more than 30 days of activity and 500 edits. Also the name of a filter in ERI projects. On English Wikipedia, this category corresponds to Extended Confirmed.

General and wiki concepts relevant to ERI

Artificial Intelligence: ERI uses predictive filters powered by the artificial intelligence (AI) program ORES. Colloquially, the term artificial intelligence is applied when a machine mimics cognitive functions that humans associate with other human minds, such as natural language processing, problem solving or learning. AI is a broad term that’s closely associated with the more specific concept of “machine learning”.
Machine Learning: Machine learning is a subfield of artificial intelligence that seeks to give computers the ability to learn tasks they haven’t been specifically programmed to do. ERI uses predictive filters powered by the machine-learning program ORES.
Accuracy: ERI tools offer AI predictive filters at various levels of “accuracy”. Used in this context, accuracy refers to the percentage of search results the filter returns that correctly identify the property the filter is targeting. In other words, the more accurate the filter is, the fewer false positives it produces. (In the AI field, the correct technical term for this is “precision”.)
Feed: Also referred to as a Stream; A computer feed is a data format used for providing users with frequently updated content. In ERI, ReviewStream is a feed that broadcasts data about recent changes to anti-vandalism and edit-review programs.
Good faith: ERI projects offer User Intent filters, which predict whether an edit was made in good faith. In this sense, the term refers to whether a user’s intention was to contribute to the wiki or damage it. A key goal of ERI is enabling reviewers to find and help editors — especially newcomers — who are trying to contribute in good faith but who may lack the skill or knowledge to do so successfully. (ERI’s User Intent filters are powered by the machine-learning program ORES, which includes a good-faith test.)
Damage: ERI projects offer Contribution Quality filters, which predict whether an edit improves the wiki or damages it. In this sense, “damage” is a general term that covers both vandalism and unintentional errors of formatting, style, fact, etc. A key goal of ERI is enabling reviewers to find and help editors — especially newcomers — who are trying to contribute in good faith but whose lack of skill or knowledge leads them to cause damage. (ERI’s User Intent filters are powered by the machine-learning program ORES, which includes a “damaging” test.)