So we just have been talking about social contagion on networks, and how
some things spread on networks, and other things try,
and never take a foothold.
Next, we're going to, maybe think about together
what are good examples of this.
And maybe the number one classical example that's easy to think about
is how Facebook got started.
So Facebook spread out of that social network for Harvard students.
That's a tight-knit group of students, same age, or friends with each other.
And as we explained, there's a small part
of the network, when this was popular, and then
it just went and eventually spread out.
And now it's incredibly popular across the world.
This is a good way for a contagion to start,
but not all contagion works out this way.
The social network I personally have been member of
is something called iWiW.
That's a Hungarian social network.
It's still there, and still reasonably popular in Hungary.
But unlike Facebook, it didn't actually spread outside of Hungary
and become popular across the world.
Some of these technologies eventually vanish and no longer work,
and others coexist and multiple different technologies some people use.
Some people use this, some people use that, some people combine them.
And this is what we wanted to help you understand throughout the course.
So this is the sort of thing that firms think about a lot.
Facebook is a great example, but in terms
of trying to introduce a new product, actually many different products,
firms often think about how to market it,
and in particular who to market it to.
Who do you want to try to get to adopt your product initially?
How does their position and their social network
affect whether your product is going to spread and survive, or actually
die out?
That basically whole area is called viral marketing, which
is how do you get this going, and thinking about contagion
and social networks is a really nice way to get it started.
And it isn't just high tech stuff.
You could be convincing farmers to adopt new agricultural practices,
or people who have adopted public health practices.
And he has this question of trying to find people who will start it out,
and then maybe [INAUDIBLE] see what their friends are doing.
Yeah, so actually there's been an analysis done
of exactly this issue in terms of getting farmers
to adopt new varieties of seed corn, trying to think about exactly how you
want to get things started so that the variety that is in fact better
actually comes to dominate.
Sometimes the innovation isn't even in technology.
If I think about how does protesting going
in a politically repressive society.
So how is it that 10,000 people or 100,000 people
turned out for protests on the same day.
That can't be everyone looking at the whole population
saying I'm going to mass [INAUDIBLE] because so far, no one's doing it.
You need that sort of small group that nucleates around in it
in a [? crescent. ?] Then when people have done research
on political protesters, the role of knowledge about what others
are likely to do plays a particularly key role-- it's true in technology
also-- but you think, if 10,000 people really show up to protest,
I should join them in the [INAUDIBLE] But if 20 people show up to protest,
well, I'll just get arrested.
Right.
And so there's sort of this thinking about what other people--
So protest is a place where you're targeting
a special segment of the population.
You get a protest about an issue, you're trying
to reach as many people who might be on your side of the issue
to show up for the protest, but you're not targeting the whole population.
So this happens in technology too.
Some technology becomes common in certain segments, certain companies,
or startup companies use certain products,
and other companies use other products.
Even in the US, we use a different system than Europeans
in measuring distances.
You use miles, I use kilometers, and you drive
on one side of the road, the English drive on the other side of the road.
There are all kinds of places where, somehow, there
is a boundary between two technologies and two adaptions.
And it stays that way, stays that way for long, long time.
Maybe forever.
So it isn't actually like one way it spreads and washes
over the whole world, and you end up getting very long-lived coexistence.
Languages are a big example.
And so it's interesting to think about when is coexistence going to end.
What is it that causes the thing to settle down
into a pattern of coexistence?
I guess I would say what's nice is, some of these models, earlier in the course,
have given us some way of thinking about when there's coexistence,
there's often kind of a boundary between the two.
But it's certainly, I would say, still sort of a mystery,
in any given situation, exactly what's going to happen.
And it's interesting both about coexistence,
and which products or conventions actually survive, and can coexist.
Part of what we've seen in other examples
is that there's no reason why a product that's necessarily better
actually is the one that wipes out everything else.
Coexistence of products, where people just
simply disagree about which one's better.
Or even when, actually, at the end, everyone sort of
agrees that something would have been better
given the amazing popularity of the not so good product.
There is so much peer effect that it's easier
and more natural to use the thing that is less good.
Then they all end up using it, despite the fact
that the comparison is just clear.
The wrong product won, basically.
That can happen.
And it gets back to some of the issues [INAUDIBLE]
[? but ?] the inherent unpredictability of these things.
There is always the danger that you take any story, the success of Facebook,
the success of the uprising, and then you say,
here's why this was inevitable.
Of course, it was never inevitable.
They were often a whole bunch of accidental decisions.
The [? plan of that. ?] That's obviously what
makes some of this very challenging to try to model.