Research:Item Recommendations for Wikidata Editors

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Created
18:20, 19 January 2022 (UTC)
Contact
Kholoudsaa (talk) 18:20, 19 January 2022 (UTC)
Collaborators
Elena Simperl and Miaojing Shi
Duration:  2019-July – 2023-03
Recommendation system - Wikidata Community - Items Recommendations
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This page documents a research project in progress.
Information may be incomplete and change as the project progresses.
Please contact the project lead before formally citing or reusing results from this page.


This project develops a recommender system that recommends Wikidata items to editors based on their past editing activities. The work is motivated by Wikidata's quest for more and more engaged editors to keep up with the knowledge graph of growing size and complexity. The aims of the projects: - Create a foundation for understanding how Wikidata items can be recommended to the editors, Examine whether implementing a recommender system helps editors and increases their engagement.

Methods[edit]

The project will consist of the followings steps: 1- Interview study with Wikidata editors to explore their current practices into how to choose that they work on, and elicit their preferences and needs. 2- Develop the recommendation model accordingly 3- Evaluate the model using offline evaluation (on a dataset) as well as online evaluation with real editors. The link to the interview questions is: https://docs.google.com/document/d/1flMpstjFbzlD_AfMTsKM0Ry985jLPGo4eV6vZHi_hJ4/edit?usp=sharing


Policy, Ethics and Human Subjects Research[edit]

The interview study and online evaluation was approved by the local committee of the developers' institution (King's College London), with the registration confirmation reference number, MRSP-20/21-23336