Hoi,
I hope it will be inspiring.. We do know that challenges work. Mrs Chen
describes that involvement has people contribute more. It had me thinking
and I wrote this blog post. [1]. To prepare for follow up activities in
both WIkidata and Wikidata, I added the winners for "Thanks for the book",
I added dates for the last 5 and I added the university the 2014 winner
went to and added fellow alumni in Wikidata.
We can pose challenges, I did that in my blogpost. I know of many other
examples where we can engage our community to do better by bringing the
challenge to them. Writing the new article that will be most read in the
next month for your language is one. This notion that by posing targeted
challenges is nothing new. What will be new is when this becomes a best
practice. When we make the data we have WORK for us.
Thanks,
GerardM
[1]
On 13 November 2014 17:51, Aaron Halfaker <ahalfaker(a)wikimedia.org> wrote:
Hey folks,
This month we're holding a special edition of the Research and Data
showcase
<https://www.mediawiki.org/wiki/Analytics/Research_and_Data/Showcase>.
We've invited Dr. Yan Chen, Professor from the UMuch iSchool to present her
work studying community dynamics with Kiva (micro-lending platform) and
what her results might imply for Wikimedia's sites. To take advantage of
her travel schedule, we'll be holding the event on *Friday** November 14
at 11.30 PST (UTC-8) *rather than the usually 3rd Wednesday. The event
will be live streamed and recorded as usual. You can join the conversation
via IRC on
freenode.net in the the #wikimedia-research channel.
We look forward to seeing you there,
-Aaron
*Does Team Competition Increase Pro-Social Lending? Evidence from Online
Microfinance.*By Yan Chen <http://yanchen.people.si.umich.edu/>In the
first half of the talk, I will present our empirical analysis of the
effects of team competition on pro-social lending activity on
Kiva.org, the
first microlending website to match lenders with entrepreneurs in
developing countries. Using naturally occurring field data, we find that
lenders who join teams contribute 1.2 more loans per month than those who
do not. Furthermore, teams differ in activity levels. To investigate this
heterogeneity, we run a field experiment by posting forum messages.
Compared to the control, we find that lenders from inactive teams make
significantly more loans when exposed to a goal-setting message and that
team coordination increases the magnitude of this effect.In the second
part of the talk, I will discuss a randomized field experiment we did in
May 2014, when we recommend teams to lenders on Kiva. We find that lenders
are more likely to join teams in their local area. However, after joining
teams, those who join popular teams (on the leaderboard) are more active in
lending.
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