Exploring and Eliciting Needs and Preferences from Editors for Wikidata Recommendations

TL;DR

This paper investigates the needs and preferences of Wikidata editors to inform the design of a recommendation system aimed at improving editor engagement and retention.

Contribution

It provides a mixed-methods analysis combining interviews and edit data to identify user requirements for a Wikidata recommender system.

Findings

Identified key editor needs and preferences for recommendations.

Outlined design requirements for an effective Wikidata recommender.

Provided insights to enhance editor engagement and retention.

Abstract

Wikidata is an open knowledge graph created, managed, and maintained collaboratively by a global community of volunteers. As it continues to grow, it faces substantial editor engagement challenges, including acquiring new editors to tackle an increasing workload and retaining existing editors. Experiences from other online communities and peer-production systems, including Wikipedia, suggest that recommending tasks to editors could help with both. Our aim with this paper is to elicit the user requirements for a Wikidata recommendations system. We conduct a mixed-methods study with a thematic analysis of in-depth interviews with 31 Wikidata editors and three Wikimedia managers, complemented by a quantitative analysis of edit records of 3,740 Wikidata editors. The insights gained from the study help us outline design requirements for the Wikidata recommender system. We conclude with a discussion of the implications of this work and directions for future work.