Wikimedia Research/Showcase/Archive/2018/05
May 2018
[edit]08 May 2018 Video: YouTube
- Case studies in the appropriation of ORES
- By Aaron Halfaker, Wikimedia Foundation
- ORES is an open, transparent, and auditable machine prediction platform for Wikipedians to help them do their work. It's currently used in 33 different Wikimedia projects to measure the quality of content, detect vandalism, recommend changes to articles, and to identify good-faith newcomers. The primary way that Wikipedians use ORES' predictions is through the tools developed by volunteers. These javascript gadgets, MediaWiki extensions, and web-based tools make up a complex ecosystem of Wikipedian processes -- encoded into software. In this presentation, Aaron will walk through a three key tools that Wikipedians have developed that make use of ORES, and he'll discuss how these novel process support technologies and the discussions around them have prompted Wikipedians to reflect on their work processes.
- By Aaron Halfaker, Wikimedia Foundation
- Exploring Wikimedia Donation Patterns
- By Gary Hsieh, University of Washington
- Every year, the Wikimedia Foundation relies on fundraising campaigns to help maintain the services it provides to millions of people worldwide. However, despite a large number of individuals who donate through these campaigns, these donors represent only a small percentage of Wikimedia users. In this work, we seek to advance our understanding of donors and their donation behaviors. Our findings offer insights to improve fundraising campaigns and to limit the burden of these campaigns on Wikipedia visitors.
- By Gary Hsieh, University of Washington