- [Yan] It's good that we have an army of enthusiasts
writing Wikipedia articles,
but sometimes when it concerns a disease that I might have,
I really want the experts' input.
♪ [music] ♪
Wikipedia is one of the most important references for the general public.
It's actually one of the most top five most visited websites in the world.
Everyone reads Wikipedia articles, but sometime you spot an error
or you say, "Well, this is not really correct."
But you move on
and say, "Someone else might fix it."
That's called the "free rider problem."
The success of Wikipedia has been really surprising
for economists because it relies purely on volunteer labor.
The medical profession has found that patients tend to bring printouts
of Wikipedia articles to their doctor's office.
Some of these articles are low quality
because they were not written by experts.
We're trying to figure out what are the some of the motivators
to get experts to contribute to high quality content.
So we decided to do a field experiment to tease out the causalities,
to figure out what motivates people to contribute to Wikipedia,
whether it's social impact or private benefit
or public acknowledgement or a combination of these factors.
So in this study, in this field experiment,
we contacted about 4,000 academic economists.
We have a generic message
that says Wikipedia is a very valuable public good,
and yet lots of the articles are inaccurate or not up to date.
Would you spend 10 to 15 minutes commenting
on these Wikipedia articles?
Then we vary the paragraphs depending on whether
they're in the treatment or control group.
In the control group, we don't mention that the articles
might cite your research.
And in the private benefit we say they might cite your research,
and we have another condition which says, "We will publicly
acknowledge your contributions."
Simply asking the expert, "Would you contribute?"
you get pretty high response rate,
which is about 45% of the people say, "Yes, I'm willing."
When we send out the links, it turns out a third of the people
actually contributed, and we look at what are the features
that predict contributions,
it turns out that if the article is really