Wikipedia: How to Motivate Expert Contributions? (Yan Chen, University of Michigan)

- [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