[Wikimedia-l] [Wikimedia Research Showcase] February 19, 2020: The Humans and Bots of Wikipedia and Wikidata

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[Wikimedia-l] [Wikimedia Research Showcase] February 19, 2020: The Humans and Bots of Wikipedia and Wikidata

Janna Layton
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:

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

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

Janna Layton (she, her)
Administrative Assistant - Product & Technology
Wikimedia Foundation <https://wikimediafoundation.org/>
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