Hi everyone,
The next research showcase will be live-streamed this Wednesday, May 13 at
11.30 PT. The streaming link will be posted on the lists a few minutes
before the showcase starts and as usual, you can join the conversation on
IRC at #wikimedia-research.
We look forward to seeing you!
Leila
This month
*The people's classifier: Towards an open model for algorithmic
infrastructure*
By Aaron Halfaker <https://www.mediawiki.org/wiki/User:Halfak_(WMF)>
Recent research has implicated that Wikipedia's algorithmic infrastructure
is perpetuating social issues. However, these same algorithmic tools are
critical to maintaining efficiency of open projects like Wikipedia at
scale. But rather than simply critiquing algorithmic wiki-tools and calling
for less algorithmic infrastructure, I'll propose a different strategy --
an open approach to building this algorithmic infrastructure. In this
presentation, I'll demo a set of services that are designed to open a
critical part Wikipedia's quality control infrastructure -- machine
classifiers. I'll also discuss how this strategy unites critical/feminist
HCI with more dominant narratives about efficiency and productivity.
*Social transparency online*
By Jennifer Marlow <http://www.aboutjmarlow.com/> and Laura Dabbish
<http://www.lauradabbish.com/>
An emerging Internet trend is greater social transparency, such as the use
of real names in social networking sites, feeds of friends' activities,
traces of others' re-use of content, and visualizations of team
interactions. There is a potential for this transparency to radically
improve coordination, particularly in open collaboration settings like
Wikipedia. In this talk, we will describe some of our research identifying
how transparency influences collaborative performance in online work
environments. First, we have been studying professional social networking
communities. Social media allows individuals in these communities to create
an interest network of people and digital artifacts, and get
moment-by-moment updates about actions by those people or changes to those
artifacts. It affords and unprecedented level of transparency about the
actions of others over time. We will describe qualitative work examining
how members of these communities use transparency to accomplish their
goals. Second, we have been looking at the impact of making workflows
transparent. In a series of field experiments we are investigating how
socially transparent interfaces, and activity trace information in
particular, influence perceptions and behavior towards others and
evaluations of their work.