Mobile design/Micro contributions

This document describes ideas for potential small contributions for mobile site users.

Rationale
Editing Wikipedia is a difficulty activity, made even more so on mobile. At the same time, there are a variety of small maintenance tasks that benefit the encyclopedia and are fun and easy to do, but that are not surfaced or presented well enough for new users to discover and use. Isolating some of these tasks and wrapping them in a user-friendly UI could be a way for new or casual users who are looking to do small, self-contained chunks of work to add significant value to the encyclopedia without having to input text or learn wiki markup.

Micro contributions may be a hook to entice users to create an account, or a benefit that they get post-signup. More research is required to determine if they are more suitable as part of a page-centric workflow (e.g., they appear naturally as part of a casual reader's exploration of content), a queue-centric one (e.g., there is an explicit call to action presented to users to go to a separate work queue or download an app designed specifically for limited micro contribution activity), or a hybrid of the two (e.g., the user tries and successfully completes one micro contribution, after which he/she receives a call to action to visit a separate queue/download an app for more tasks).

User research
Maintenance tasks are very popular among experienced editors on the desktop site&mdash;many of whom use community-built tools like the Dab solver or HotCat to effectively build their own work queues of micro contribution.

In the month of October 2012, there were 16,256 revisions using the Dab solver tool on English Wikipedia, with 627 unique editors using the tool. To compare this to another popular semi-automated tool among experienced editors: there were 14,446 Huggle warnings issued in September 2012, with a total of 114 unique editors using the tool. The high editor-to-revision ratio suggests that a small number of experienced users are hooked on this tool and return to it often to perform batch disambiguation actions.

User stories

 * As a new or casual Wikipedia user, I want a quick, easy way to contribute productively to the encyclopedia.

Design requirements

 * Create micro contribution features that don't require text input
 * Use elements of incentive-centered design to encourage good contribution
 * Leverage existing work queues on Wikipedia where possible

Categorizing

 * add/remove/manage categories on articles (see HotCat)

Page-centered flow:
 * 1) User comes to an article via Google search
 * 2) User sees section with categories that the article is a part of
 * 3) User sees link to add/remove categories

Queue-centered flow:
 * 1) User comes to an article via Google search (mobile frontend) or accesses Wikipedia directly (mobile application)
 * 2) User gets a call to action to visit a separate work queue (Category:Uncategorized pages)
 * 3) User sees list of articles that need categories and can add them

Disambiguation

 * fix links to disambiguation pages by selecting the appropriate article from a list of suggested ones (see screenshots of the Dab solver tool on desktop below)

Page-centered flow:
 * 1) User comes to an article via Google search
 * 2) User sees a link that is styled differently from other internal links
 * 3) User taps and gets a popup asking him/her where this link should go. E.g. "... and the main character experiences a flashback." ← Should this link go to: Flashback (narrative) or Flashback (psychology)?
 * 4) User can dismiss the notice or choose to accept the task

Queue-centered flow:
 * 1) User comes to an article via Google search (mobile frontend) or accesses Wikipedia directly (mobile application)
 * 2) User sees call to action to visit a separate work queue (Category:Articles with links needing disambiguation)
 * 3) User sees list of articles with links that need disambiguating and can do as many as he/she wants


 * Current workflow on desktop

Wikifying

 * tap words to add/remove an internal link

Page-centered flow:
 * 1) User comes to an article via Google search
 * 2) User sees a suggested internal link under a word that should probably be wikified
 * 3) User taps the word, which creates a link
 * 4) User can untap a word to remove a link

Queue-centered flow:
 * 1) User comes to an article via Google search (mobile frontend) or accesses Wikipedia directly (mobile application)
 * 2) User sees call to action to visit a separate work queue (drawn from Category:Articles that need to be wikified)
 * 3) User can select an article and add/remove internal links where appropriate

Article feedback
Revision-level
 * (from the watchlist) +1 good edits
 * (from the watchlist) downvote/flag bad edits

Article-level feedback
 * +1 an article
 * Thank the Author/Editors

Image curation
As part of the Photo uploads project, there are potential avenues for adding curation micro-contributions like: Tagging people in photos based on wikidata information
 * add categories to your image/ add categories to all images
 * add geo-coordinates to your image/ add geo-coordinates to all images

Recent changes patrol

 * revert or give revision level feedback on new changes

New Pages Feed

 * review & tag new articles for cleanup
 * add categories to newly created articles

Quality crowdsourcing
Quality control
 * Images
 * up/down vote if a specific image belongs in an article
 * up/down vote image on quality
 * up/down vote images on appropriateness/relevance for a category
 * rank images within an article to choose lead image

Article Workflows
 * vote on whether an article should be deleted
 * highlight sections of article as needing references (mobile)
 * highlight section of article to quick add reference from ISBN or URL (mobile)

Location-based edits

 * Attaching GPS coordinates to an article or image
 * This could be ideal from mobile
 * Aggregate photos from Commons that were taken near a geo-located article and display as as a gallery
 * Prompt users to upload image when geographically near an article missing an image
 * Prompt user to associate an image with their current location if the article does not have a location when mobile.
 * Match articles to Open Street Maps, Facebook, Foursquare locations

Category ontology

 * given two categories choose weather they have a parent child relationship or not
 * given a multi-word category decide if each separate word matches existent categories
 * “United States Finance” → “United States” & “Finance”
 * Merging categories thats should be merged “United States” → “United States of America”
 * Sorting categories on an article by importance
 * Choosing primary category for an article