Article feedback/Extended review

Because of the lack of a standard, readily-available tool to create and store quality reviews of Wikipedia content, several groups and organizations have created their own ad-hoc tools for this purpose. This page describes a standard system for such organizations to conduct open quality review of Wikipedia content, and surface the results on the article page.

This system is primarily intended for Wikipedia, but could also be used on other Wikimedia projects.

System

 * What form does the system take?

A MediaWiki extension is the easiest implementation form for the review system: it will make integration with Wikipedia user accounts easier, and review data will be stored locally. The Article feedback tool provides an existing framework that could be extended to support a more detailed quality review process.

Authentication

 * How does a credentialed reviewer authenticate?
 * How can the authentication process be scaled / automated? (use case: mass outreach from organizations to their members)

E-mail is the safest assumption we can make on the partner organization's infrastructure.

Organization members get an invitation by e-mail to confirm their affiliation to the organization on Wikipedia; the invitation contains a link that leads them to a special page to confirm their affiliation. The link contains a token to identify the partner organization (mandatory), and if possible other information to prefill the fields.


 * If the user is logged in, the page displays the fields required for the confirmation. If they want to use an alternate account for
 * Organization (non-editable, filled)
 * Real name (mandatory, editable, filled if possible)
 * Credentials (optional, editable, filled if possible)
 * Link to university page or biography (optional, editable, filled if possible)
 * If the user isn't logged in, the page offers the possibility to log in in-place, or sign up in-place. When that is done, it displays the interface for logged-in users.

If the partner organization agrees to provide us with a structured document containing this information (e.g. a CSV file), a script can be run to generate these e-mail invitations.

If the partner organization prefers not to share this information with us, we would provide them with a modified script that would only identify the organization; their members would then enter the rest of the information themselves.

The reviewer should be able to attach their existing Wikipedia account if they have one, instead of creating a new one.

Review location and submission

 * Who decides who reviews what?
 * How is the review submitted?

A voluntary model, where people can review any page they want, is the simplest implementation, and the most likely to fit within the existing article feedback infrastructure. Restricting the scope of reviewable articles doesn't appear to be necessary: existing expert review systems show that reviewers usually stick to their field of expertise when their name is publicly associated with the review.

Because articles can grow fairly long, it would be better to allow the reviewer to scroll through the article while they're reviewing it, while keeping the review fields always visible (some suggested a setup similar to common the fixed-position "feedback tab").

Specifics of implementation
The following locations can be considered for the tool:
 * at the bottom of articles (current location of the article feedback interface)
 * in the left sidebar (this might not be very visible)
 * as a fixed panel (top, bottom or side of the browser window) that doesn't move when scrolling.

Testing these locations and comparing their success will help determine which one is best. Criteria may be: user engagement, quality of reviews, community perception.

Regardless of the implementation, it is strongly recommended that the review interface not hide the content reviewed; the reviewer needs to be able (this means the review shouldn't be displayed in a modal overlay). Furthermore, the interface will likely need at least two states of expansion (collapsed & unfolded).

Review content

 * What is the content of the actual review?

Preliminary considerations
Analysis of the Article feedback experiment shows that Wikipedians have a consistent grasp of what criteria like "neutrality" and "well-sourced" mean, and rate them fairly consistently. The general public, however, who accounts for about 95% of the feedback provided, doesn't have the same model and provides ratings that vary greatly.

For the same reason, readers rarely rely on numeric ratings like Likert scales, as suggested by UX research on the current Article feedback tool. They're more interested in reading well-built reviews. They're also interested in information about who the reviewer is, so as to gauge the relevance of the comment/review for their personal situation.

Some criteria, like the well-sourcedness of an article, can be assessed by an aggregate of automated quantitative metrics (like the number of references relative to the length of the article) and human-generated qualitative feedback (like the appropriateness of the references, and their reliability).

Based on these considerations, it appears it would be better to move to a system where the reviewer is invited to answer a series of questions (some open-ended) to help readers and editors identify possible issues (and thus areas of improvement) with the article.

"Simple" readers and subject-matter "experts" (whether they're credentialed or not) have a different use for the article, and can provide different levels of feedback. A reader's main purpose may be to quickly find a specific piece of information, while an expert may want to check that the quality of the whole article. Asking the reviewer if they believe to have knowledge on the topic could be used to ask different questions, relevant to each profile.

Possible questions & issues

 * Provide feedback
 * Do you consider yourself particularly knowledgeable on this topic? (yes/no)
 * (If not)
 * Did you find what you were looking for? (yes/no)
 * Report an issue with this article (form TBD)
 * Thank the authors (free text)
 * (If yes)
 * Would you recommend this article to a student, or for inclusion in a book?" (yes/no)
 * General assessment that can act as a "binary flag" for other purposes, like selective inclusion in collections
 * (If yes)
 * Would you like to compliment the authors? (free text)
 * (If not)
 * You have identified issues with: (checkboxes)
 * Completeness: The article doesn't provide an exhaustive coverage of the topic.
 * Readability: the article contains bad English, inappropriate grammar, vocabulary, etc.
 * Organization: The article isn't well-structured, or doesn't flow well.
 * Neutrality: The article contains opinionated material, or undue weight is given to a subtopic.
 * Verifiability: The article contains too few or too many references, or they're inappropriate or unreliable.
 * Illustration: The article contains too few or too many illustrations, or they're inappropriate.
 * Other
 * ''When an issue is checked, a free-text field is enabled for the reviewer to provide more information.

Specifics of implementation
Implementation choices may be:
 * whether or not to include a Likert scale; for example, clicking stars may help with user engagement, even if the results are not terribly useful.
 * whether review items should be single words ("Completeness"), questions ("Does the article provide an exhaustive coverage of the topic?"), statements of issues ("The article doesn't provide an exhaustive coverage of the topic."), or a combination of them. User engagement, as well as consistency and quality of reviews, will be the determining factors.
 * the amount of review items, and the overall length of the review, depending on how it impacts user engagement, completion rate and the quality of reviews.
 * how to best encourage the reviewer to improve the page themselves
 * whether or not to allow the reviewer to disclose a conflict of interest (e.g. if they have significantly edited the article themselves, which could be automatically assessed, or if they're particularly biased on the topic itself).



Review publication

 * Where and how is the review published?
 * How are useful reviews surfaced, and useless or off-topic reviews handled?

Preliminary considerations
There are multiple reasons to integrate reviews with the existing talk page framework:
 * The talk page is the appropriate place to discuss improvements of the article; editors who watch the page will be notified of new reviews.
 * Few readers currently know of the talk page; by making it more discoverable, more readers may realize the information it contains is useful to assess an article's quality.
 * Reviewers are likely to appreciate feedback on their review and to have a venue to discuss further with editors; the talk page provides this opportunity.

However, there is also a risk that the talk page turns into a forum, or that the sheer amount of useless or irrelevant comments overwhelm editors on the talk page. Processes will be necessary to assess the usefulness and relevance of a review/comment to the article's improvement.

Furthermore, some users may be interested in reading reviews of an article, even if they're not actionable items that belong on a talk page.

Review triage


Triagers will be responsible for assessing the incoming reviews and acting depending on their content. The goal will be to surface the particularly relevant content from the quantity of reviews.

Existing processes for treating inappropriate text (personal attacks, personally identifiable non-public information, libel, etc.) will continue to apply.

Actions available for reviews:
 * Archive: The review doesn't require follow-up, is unspecific, or mentions an issue that was resolved.
 * Move to the recycle bin: The review consists of spam, nonsense, test.
 * Mark as pending issue: The review raises an actionable issue that needs to be addressed.
 * (for administrators only) Delete / restore
 * (for valid reviews only) Promote to the talk page

Automatic actions:
 * Automatically archive praise (identified as such by the reviewer). (? no, doesn't provide an easy way to promote to talk page)
 * Automatically archive reviews that consist only of ratings (no text).

Review list
Users should have the ability to sort or filter the list of reviews for a given article, for example by date (to show the latest review first), by reviewer (to show self-identified "experts" first), by usefulness, by status, etc.

Reviews can be classified in categories, depending on their usefulness for the user:
 * new reviews
 * praising reviews
 * pending actionable reviews
 * closed reviews: contains reviews with status: invalid, no follow-up required, merged or resolved.
 * trash / recycle bin: spam, personal attacks, etc.: automatically deleted after a time, or manually before that.

Promotion of the review to the talk page
Constructive criticism and particularly relevant reviews about an article should be promoted to the talk page, for the reasons provided above. Each community will need to agree on guidelines for promoting a review to the talk page, but the


 * The review should indicate that it was promoted to the talk page, when and by whom.
 * The status of the review should remain independent from the promotion to the talk page; for example, promoting an actionable review to the talk page should keep it "pending", and not close it.
 * The text appearing on the talk page should contain:
 * A link to the review
 * The name of the reviewer, and date of the review
 * The free-text comment of the review
 * The name of the promoter, and date of the promotion

It seems superfluous to include numerical or binary ratings in the text that goes to the talk page, since it's really the comments that should start the discussion.

Other features

 * Public list of one's reviews: Being able to showcase one's work on Wikipedia is a factor encouraging the participation of some "experts". This could take the form of a special page (e.g. )
 * API to access the entirety of the reviews and their specifics

API

 * standards / policies for integration of data from external review systems with ours

Flags
"green flag"
 * threshold of recommendations
 * no critical issues

"neutral flag"
 * not enough data
 * non-critical issues

"red flag" (= heads-up)
 * threshold of issues reported through reviews or alert banners
 * unpatrolled edits (only on high-traffic articles?)

Temporal evolution
Some would like to be able to measure the evolution of the quality of an article over time. Quality depends very much on each reader's perspective and needs; no absolute, one-size-fits-all metric will ever satisfy all readers.

A possibility would be to plot the evolution of positive reviews against negative reviews, taking into account the changes made to the article.

Generally, it would be better to present well-designed quality information and charts, rather than an arbitrary quality index.

Possible metrics / indicators
Generic:
 * date created
 * the article was last changed X (months|days|hours|minutes) ago by X. (and hasn't been patrolled since)
 * the talk page was last changed X days ago.
 * Contributors who added the most content are: X
 * community assessment status (featured, good, stub, etc.)

over the last X days: (X = {1, 7, 30, ∞})
 * number of changes
 * number of contributors
 * number of reviews
 * number of praising comments, and breakdown by self-identified experts
 * number of issues raised, and breakdown by self-identified experts
 * number of issues raised and resolved
 * number of pending issues
 * number of readers who indicated they found what they were looking for


 * Possibly: area for warning templates (POV, etc.)
 * ratings / reviews: histograms, distribution; filtering
 * take expiry into account