An analysis of discussions in collaborative knowledge engineering through the lens of Wikidata

Research output: Contribution to journalArticlepeer-review

Abstract

We study discussions in Wikidata, the world's largest open-source collaborative knowledge graph (KG). This is important because it helps KG community managers understand how discussions are used and inform the design of collaborative practices and support tools. We follow a mixed-methods approach with descriptive statistics, thematic analysis, and statistical tests to investigate how much discussions in Wikidata are used, what they are used for, and how they support knowledge engineering (KE) activities. The study covers three core sources of discussion, the talk pages that accompany Wikidata items and properties, and a general-purpose communication page. Our findings show low use of discussion capabilities and a power-law distribution similar to other KE projects such as Schema.org. When discussions are used, they are mostly about KE activities, including activities that span across the entire KE lifecycle from conceptualisation and implementation to maintenance and taxonomy building. We hope that the findings will help Wikidata devise improved practices and capabilities to encourage the use of discussions as a tool to collaborate, improve editor engagement, and engineer better KGs.

Original languageEnglish
Article number100799
JournalJournal of Web Semantics
Volume78
DOIs
Publication statusPublished - Oct 2023

Keywords

  • Collaborative knowledge engineering
  • Discussion analysis
  • Knowledge graph
  • Wikidata

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