Wikipedia -- like most peer production communities -- suffers from a basic problem: the amount of work that needs to be done (articles to be created and improved) exceeds the available resources (editor effort). Recommender systems have been deployed to address this problem, but they have tended to recommend work tasks that match individuals' personal interests, ignoring more global community values. In English Wikipedia, discussion about Vital articles constitutes a proxy for community values about the types of articles that are most important, and should therefore be prioritized for improvement. We first analyzed these discussions, finding that an article's priority is considered a function of 1) its inherent importance and 2) its effects on Wikipedia's global composition. One important example of the second consideration is balance, including along the dimensions of gender and geography. We then conducted a quantitative analysis evaluating how four different article prioritization methods -- two from prior research -- would affect Wikipedia's overall balance on these two dimensions; we found significant differences among the methods. We discuss the implications of our results, including particularly how they can guide the design of recommender systems that take into account community values, not just individuals' interests.
- Pub Date:
- August 2022
- Computer Science - Computers and Society;
- Computer Science - Human-Computer Interaction
- To appear at the 25th ACM Conference On Computer-Supported Cooperative Work And Social Computing (CSCW 2022)