I'm stoked that you guys also see the potential here.  I look forward to continuing this discussion with Yan as her team looks to Wikipedia as a space to try out similar methods. 

I hope that I'll see you guys in #wikimedia-research. :) 

-Aaron

On Fri, Nov 14, 2014 at 2:25 AM, Gerard Meijssen <gerard.meijssen@gmail.com> wrote:
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


On 13 November 2014 17:51, Aaron Halfaker <ahalfaker@wikimedia.org> wrote:
Hey folks, 

This month we're holding a special edition of the 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
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.

_______________________________________________
Wiki-research-l mailing list
Wiki-research-l@lists.wikimedia.org
https://lists.wikimedia.org/mailman/listinfo/wiki-research-l



_______________________________________________
Wiki-research-l mailing list
Wiki-research-l@lists.wikimedia.org
https://lists.wikimedia.org/mailman/listinfo/wiki-research-l