Title: Approving Automation: Analyzing Requests for Permissions of Bots in Wikidata
Authors: Mariam Farda-Sarbas (Freie Universitat Berlin), Hong Zhu (Freie Universität Berlin), Marisa Nest (Freie Universität Berlin), Claudia Muller-Birn (Freie Universität Berlin)
Abstract: Wikidata, initially developed to serve as a central structured knowledge base for Wikipedia, is now a melting point for structured data for companies, research projects and other peer production communities. Wikidata’s community consists of humans and bots, and most edits in Wikidata come from these bots. Prior research has raised concerns regarding the challenges for editors to ensure the quality of bot-generated data, such as the lack of quality control and knowledge diversity. In this research work, we provide one way of tackling these challenges by taking a closer look at the approval process of bot activity on Wikidata. We collected all bot requests, i.e. requests for permissions (RfP) from October 2012 to July 2018. We analyzed these 683 bot requests by classifying them regarding activity focus, activity type, and source mentioned. Our results show that the majority of task requests deal with data additions to Wikidata from internal sources, especially from Wikipedia. However, we can also show the existing diversity of external sources used so far. Furthermore, we examined the reasons which caused the unsuccessful closing of RfPs. In some cases, the Wikidata community is reluctant to implement specific bots, even if they are urgently needed because there is still no agreement in the community regarding the technical implementation. This study can serve as a foundation for studies that connect the approved tasks with the editing behavior of bots on Wikidata to understand the role of bots better for quality control and knowledge diversity.