Hi all,
The next Research Showcase will be live-streamed on Wednesday, February 19, at 9:30 AM PST/17:30 UTC. We’ll have presentations from Jeffrey V. Nickerson on human/machine collaboration on Wikipedia, and Lucie-Aimée Kaffee on human/machine collaboration on Wikidata. A question-and-answer session will follow.
YouTube stream: https://www.youtube.com/watch?v=fj0z20PuGIk
As usual, you can join the conversation on IRC at #wikimedia-research. You can also watch our past research showcases here: https://www.mediawiki.org/wiki/Wikimedia_Research/Showcase
This month's presentations:
Autonomous tools and the design of work
By Jeffrey V. Nickerson, Stevens Institute of Technology
Bots and other software tools that exhibit autonomy can appear in an organization to be more like employees than commodities. As a result, humans delegate to machines. Sometimes the machines turn and delegate part of the work back to humans. This talk will discuss how the design of human work is changing, drawing on a recent study of editors and bots in Wikipedia, as well as a study of game and chip designers. The Wikipedia bot ecosystem, and how bots evolve, will be discussed. Humans are working together with machines in complex configurations; this puts constraints on not only the machines but also the humans. Both software and human skills change as a result. Paper
When Humans and Machines Collaborate: Cross-lingual Label Editing in Wikidata
By Lucie-Aimée Kaffee, University of Southampton
The quality and maintainability of any knowledge graph are strongly influenced in the way it is created. In the case of Wikidata, the knowledge graph is created and maintained by a hybrid approach of human editing supported by automated tools. We analyse the editing of natural language data, i.e. labels. Labels are the entry point for humans to understand the information, and therefore need to be carefully maintained. Wikidata is a good example for a hybrid multilingual knowledge graph as it has a large and active community of humans and bots working together covering over 300 languages. In this work, we analyse the different editor groups and how they interact with the different language data to understand the provenance of the current label data. This presentation is based on the paper “When Humans and Machines Collaborate: Cross-lingual Label Editing in Wikidata”, published in OpenSym 2019 in collaboration with Kemele M. Endris and Elena Simperl. Paper
--