Reading/Web/Content Discovery Experiments/Updates

October 2024: Introducing the experiments

Hi everyone! This fiscal year (which began in July 2024), together with the Apps team, we are working on Content Discovery. The motivation is to better retain a new generation of readers to our sites. Learn more about this broader cross-team project.

As the first steps on this project, our team is conducting a few feature experiments. We have planned to run them between July and December. In general, they are focused on making content easier to discover and learn from. Specifically, they are about improving the browsing experience and helping readers learn, using recommendations, content summarization, and new interface designs.

Some of these experiments include machine generated recommendations or summarized content, while others focus more on highlighting editor-curated work or remixing content in various ways. (To learn more, see the notes from our Wikimania brainstorming session.)

The code, design, and implementation of these experiments are all temporary – we'll use the data collected and any opinions we receive from communities and readers to determine what next steps for these ideas will be. Tentatively, we expect to choose one or two of the four ideas, iterate and update it based on what we learn, and continue to scale into a feature on a few pilot wikis.

Recently, we have released a second experiment in the Wikipedia Recommender browser extension. This is a simple experiment that will show participants recommendations while reading. We will study the overall usage of extension features and use the data collected to inform whether we want to bring this, or a similar feature, into production on some of our pilot wikis. If you're interested in helping us test and are using a supported browser, we welcome you to download the extension and give us your feedback! (We hope to extend browser support further in the future as well – we'll message out more about this when we have more concrete dates.)

To learn more details about the experiments themselves, check out our documentation. We'd be especially curious in your opinions on these specific ideas as a starting point to improving content discovery and learning on the wikis. In addition, we'd be happy to hear any ideas you have in this area that we could potentially scale into an experiment in the future. Thank you!