Wikimedia Apps/Team/Android/Image Recommendations

Background
In May 2021 the Android team built an MVP for Image recommendations. The goal of the MVP was to determine if it would be a good* task for newcomers, especially on mobile. The results were generally positive resulting in the Growth team introducing the feature on Web (Desktop and Mobile). It has had mostly positive results and the community is acquainted with the feature giving us the confidence to bring the feature back to the app with the ability to actually post photos.

Requirements
As we strive to provide an intuitive and rewarding experience for our users, we have defined a set of fundamental requirements for V1 of our application, along with a number of desirable enhancements that we aspire to implement in the future.

Essentials for Version 1
The entry point for users should be located both on the 'Suggested Edits' screen and within an article.


 * 'Image Recommendations' task should be positioned immediately below 'Article Descriptions'.
 * A new task indicator should be available for users who have already completed at least one suggested edit. This indicator should disappear upon their second visit.
 * While users should have the option to add captions, they will not be prompted to do so. Users must have an accessible avenue to report feature-related issues, which will lead them to our support email.
 * A link to the FAQ page should be included within the task.
 * Measures should be in place to prevent users from repeatedly confirming edits within short intervals (less than 5 seconds) to guard against misuse.
 * New users will be guided through an onboarding process for the feature.
 * Users should have the ability to access the full article and image metadata. Users cannot skip tasks without providing some form of feedback (Yes, No, Not Sure).
 * The functionality for users to zoom/pinch on the image should be included.
 * Provisions need to be made for scenarios when images run out or tasks are unavailable in certain languages.

Nice to Haves

 * Enabling users to filter tasks by topics. Incorporation of subtle positive reinforcement messages (displayed in dark mode).

Potentially out of scope

 * Addition of section images.

Target Wikis
We aim to concentrate on the following key quant regions and languages for our study:


 * 1) Spanish Wikipedia
 * 2) Portuguese Wikipedia
 * 3) Persian Wikipedia
 * 4) Hindi Wikipedia (or alternatively, Bengali Wikipedia, subject to API compatibility)

Our targeted qualitative audience comprises:


 * 1) Spanish and Portuguese-speaking individuals within LATAM and Caribbean countries.
 * 2) Hindi speakers residing in India.
 * 3) Persian speakers distributed across the diaspora.

In our study, we are committed to fostering a balanced and diverse group of testers. To that end, we aim for a broad spectrum of gender representation, ensuring that all perspectives are well-captured and accounted for.

Validation

 * KR 1.1: 2000 articles have images in a 30 day period
 * KR 1.2: Average at least 8 edits per session per unique user
 * KR 1.3: 15% of Suggested Editors try image recommendations task
 * KR 1.4: 70% of those users complete the task again on a separate day in a 15 day period
 * KR 1.5: At least a 35% task completion rate
 * KR 1.6: DAU of Suggested Edits increase overall

Guardrails

 * KR 1.1: Feature does not worsen gender or geographic bias*
 * KR 1.2: Less than 5% of users report NSFW or offensive content
 * KR 1.3: Users spend at least 10s evaluating a task before publishing it
 * KR 1.4: Bounce rate does not exceed 50%
 * KR 1.5: Reject and Accept rate does not deviate from Mobile Web or MVP by more than 10%
 * KR 1.6: Revert rate does not exceed 15%

Curiosities

 * KR 1.1: Do these numbers differ by language or user tenure
 * KR 1.2: If this is a user’s first suggested edit, do they go on to try others?
 * KR 1.3: Feature perception by geographically underrepresented groups on large language wikis

Image Recommendations Experiment

 * We embarked on an ambitious experiment aimed at enhancing the user experience of its Android app. This can be read on the experiment project page. The initiative, driven by the Android team in collaboration with the Platform Engineering Team, sought to introduce a new feature: image recommendations. The concept involved suggesting relevant images to articles within the Wikipedia app, providing a richer and more engaging user experience. This feature was developed with the goal of improving the readability and information richness of Wikipedia articles, ultimately fostering greater user interaction and community engagement.
 * The development process saw the implementation of a Minimum Viable Product (MVP), characterized by several defining features. Key among these was the provision of a single image suggestion per article and the initial absence of image captions. Additionally, the task had no language constraints, making it accessible to a diverse range of users across multiple languages. Moreover, a new API was built to facilitate the image recommendation task, while potential future iterations were also considered, including the potential for article category filtering.
 * To ensure the effectiveness of the new feature, extensive user testing was incorporated into the development process. This involved analyzing user behaviors and preferences and monitoring interaction times to gauge task difficulty. Feedback mechanisms were designed to gather responses on specific user actions, such as image rejection or skipping, to assess the occurrence of offensive or inappropriate content. As a part of the feedback loop, a survey was surfaced each time a user rejected an image match.
 * Concurrently, the Android team focused on developing user-friendly designs, which were subsequently transformed into a prototype. The design process was informed by several user stories, aiming to fulfill a range of user needs and preferences. These user needs included the discovery of new features, education about tasks, the actual image addition process, and the provision of positive reinforcement to encourage continued user engagement.
 * The Wikipedia image recommendation experiment serves as a shining example of user-centric design and development. By focusing on a feature that can significantly enhance the user experience and committing to thorough user testing and feedback analysis, the team exhibited a strategic approach to product development. The implementation of the image recommendation feature in the Wikipedia Android app may ultimately result in greater user interaction, a more vibrant community, and a richer, more engaging Wikipedia experience. As the project moves forward, it will continue to evolve, potentially bringing about even more innovative and user-friendly enhancements to the platform.

User Stories

 * As a Wikipedia Android app user with a small screen and inconsistent internet, I would like to evaluate images and determine if they should go into an article, to contribute to Wikipedia articles that are in need of more content.
 * When I am using the Android app, I want to be able to add images with one hand to many articles on my mobile device, so that I can be productive while riding the bus in Bogotà, and listening to music.
 * When I am reading an article about Allameh Jafari Bridge in Iran, I want to learn that I can add an image to the Persian language article, so that I can enhance articles that I find interesting.
 * When I try to add an image to an article and fail, I want to learn how to do this task, so that I can build my confidence before going on to adding image that I want as my intended edit.
 * BONUS: When I am recommended an image for an article in Bengali and I don’t believe the image is a good fit and I am physically next to the subject of the article, I want to be made aware there is a Commons app, so I can upload the appropriate image using the Commons App

Designs
Below are some designs that describe the work done:

1) Discovery: A tooltip points to the Edits tab. Shown in the next session after the "Did you know everyone can edit Wikipedia?" tooltip.

2) Home:


 * The "Article Images" task is added after "Article descriptions" in "Suggested edits" home
 * A "New" indicator on the first launch that the task’s been newly added

3) Onboarding: A full-screen onboarding slide informs users about the task at hand

4) - 6) Tooltips:


 * Contextual tooltips onboard the user to the task
 * Ideally, the suggestion at the bottom already starts loading so it’s ready to be displayed once users taps "Next" in the first tooltip
 * The first to two tooltips ideally use "Next" to show the next tooltips and the last one should use "Got it" as a call to action
 * A number indicator shows how many tooltips are coming at the bottom right (can be hardcoded)

7) Feed


 * Design is similar to what’s been implemented for the previous "Train image algorithm" task, but uses the updated components Image can directly be zoomed (Instagram style)
 * Tapping the card takes users to the file page (shown in 12)
 * Filename, file description, and suggestion reason should all be *truncated* after two lines to not take up too much space
 * "No" triggers a dialog with the same options as in the current Growth implementation (see screen 8)

8) Rejection dialog: Displayed when users tap "No"

9) Warning snackbar: A warning snackbar appears if users spend less than 5s evaluating a task before hitting publish

10) More menu:


 * "Tutorial" triggers take users back to screen 3
 * "Learn more" takes users to the Suggested edits FAQ page (which needs to be updated)
 * The tooltips are triggered (4-6) within the context of the current suggestion, to make it easier for the user to understand what to do

11) Sheet collapsed: Collapsed state when the bottom sheet is pulled down (exact design can be evaluated during implementation)

12) Image details:


 * This view is used to add an image via Wikitext editor. Make sure to also update the view within Wikitext editing
 * It’s using new components so it looks more consistent
 * Tapping the file information card at the top leads to the file page (screen 13)
 * It is possible to tap "Continue" without providing an image caption and alt text (secondary call to action)

13) File page: This is the existing file page. No changes are needed currently.

14) - 15) Image details active + filled: Once both fields are filled, the "Continue" button at the top turns into a primary call to action

16) Preview screen: Should look more or less like this. Depends on what’s possible from the engineering side.

17) - 18) Edit summary:


 * Is also optional (similar to image details), but we don’t encourage empty summaries by using a secondary call to action in the empty state.
 * This screen is also used already within Wikitext editing

19) Loading state: Uses the top progress indicator

20) Next suggestion:


 * Shown after the previous edit is published
 * Snackbar confirms that the edit is published
 * View takes users to the Diff page
 * Snackbar is shown above Yes, No, Not sure buttons

Technical Limitations

 * Navigating through the intricacies of our technical roadmap, there are several key limitations and challenges that we must acknowledge and address in the development of the Image Recommendations feature for our Android application.
 * The Android team, while responsible for the Image Recommendations MVP, is currently figuring out the most effective strategy for API utilization. This includes deciding whether to follow the Growth team's path of adding images to articles that lack them and having a separate task for adding images in sections, or creating a system that generally adds images to articles.
 * The technical feasibility of using GrowthExperiments as a proxy, as suggested by @kostajh and affirmed by @BPirkle in task T306349#8311919, is yet to be fully explored and determined.
 * Ideally, the team aims to achieve cross-platform synchronization. This means if a user has completed the Image Recommendations task on Mobile Web, their progress and contributions should be recognized and carried over to the Image Recommendations task in the Android app. This technical requirement might be challenging due to the need for seamless integration and data synchronization across platforms.
 * If the above-mentioned cross-platform synchronization cannot be achieved due to technical constraints, an acceptable alternative would be to make the Android app image recommendations feature clearly distinct from the mobile web version. This implies designing two distinct user interfaces and user experiences for the same task across different platforms, which could also present technical challenges.