The Wikimedia Foundation Research team established the Wikimedia Foundation Research Award of the Year in 2021 to recognize recent research that has the potential to have significant impact on the Wikimedia projects or research in this space.

2025

After reviewing over 200 candidate peer-reviewed publications from 2024 we are honored to announce the WMF-RAY 2025 winners. Read below to learn more.

Motivating Experts to Contribute to Digital Public Goods: A Personalized Field Experiment on Wikipedia (paper)

for conducting a carefully designed field experiment to better understand how to incentivize experts to contribute their knowledge to Wikipedia.

Wikipedia relies on the contributions by volunteer editors and can benefit from contributions by subject-matter experts. However, many such potential contributors do not contribute their knowledge to Wikipedia. This paper aims to answer how Wikipedia can change this.

The researchers designed a randomized controlled trial involving 3,974 academic economists. They tested various ways of inviting these experts to contribute to Wikipedia articles and showed that when the topic of the article is related to the expert’s area of expertise, the experts are more likely to say that they will contribute to Wikipedia. However, none of the different ways of asking appeared to change the rate of actual contributions to the articles. Faced with this puzzle, the researchers developed a novel statistical prediction model showing that the stronger the match between the economists and their expertise, the more likely they are to actually contribute to the Wikipedia articles.

In addition to generating over 1,000 messages posted to Wikipedia talk pages (which the authors show led to tangible article improvements), this paper offers practical guidance for how to build better outreach strategies- for Wikipedia and other digital public goods. It also showcases creative new uses of natural language processing and recommender systems to match people with meaningful contribution opportunities.

Beyond the research findings, the work reinforces the point that when we make it easier for people to see how their knowledge matters, they’re more likely to step in and help grow our projects, an important lesson for all of us in supporting more people to share in the sum of all human knowledge.

[Best Student Paper] Low-resourced Languages and Online Knowledge Repositories: A Need-Finding Study (paper)

for providing a set of insights and opportunities for improving the experience of contributors to low-resourced Wikipedia languages.

A large number of Wikipedia language editions are in what researchers call “low-resourced” languages- languages spoken by millions of people around the world but often underserved when it comes to tools, content, and support. This paper offers a rare and in-depth look at the challenges and opportunities faced by contributors to three such Wikipedias: Afan Oromo, Amharic, and Tigrinya, all spoken in Ethiopia.

The study takes a two-part approach. First, the authors analyzed talk page conversations from each of the three Wikipedias to understand the real-world hurdles faced by established contributors. They found a mix of technical and non-technical barriers- from limitations in software support to difficulties in community coordination.

Second, the researchers conducted screen-recorded editing sessions and interviews with new contributors who are fluent in these languages. This gave a window into the lived experiences of first-time editors, highlighting usability issues, language-specific challenges, and broader systemic gaps.

The paper not only documents challenges faced by the three Ethiopian languages studied, but also works to identify the broader and more general takeaways that affect both other languages and other knowledge commons.