Social Reinforcement and the butterfly effect
Gabe forwarded this to me. Very interesting.
From a New York Times piece by Duncan Watts, a professor of sociology
at Columbia University, April 15 2007:
Conventional marketing wisdom holds that predicting success in
cultural markets is mostly a matter of anticipating the preferences of
the millions of individual people who participate in them. From this
common-sense observation, it follows that if the experts could only
figure out what it was about, say, the music, songwriting and
packaging of Norah Jones that appealed to so many fans, they ought to
be able to replicate it at will. And indeed that’s pretty much what
they try to do. That they fail so frequently implies either that they
aren’t studying their own successes carefully enough or that they are
not paying sufficiently close attention to the changing preferences of
their audience.
The common-sense view, however, makes a big assumption: that when
people make decisions about what they like, they do so independently
of one another. But people almost never make decisions independently
– in part because the world abounds with so many choices that we have
little hope of ever finding what we want on our own; in part because
we are never really sure what we want anyway; and in part because what
we often want is not so much to experience the “best” of everything as
it is to experience the same things as other people and thereby also
experience the benefits of sharing.
There’s nothing wrong with these tendencies. Ultimately, we’re all
social beings, and without one another to rely on, life would be not
only intolerable but meaningless. Yet our mutual dependence has
unexpected consequences, one of which is that if people do not make
decisions independently — if even in part they like things because
other people like them — then predicting hits is not only difficult
but actually impossible, no matter how much you know about individual
tastes.
The reason is that when people tend to like what other people like,
differences in popularity are subject to what is called “cumulative
advantage,” or the “rich get richer” effect. This means that if one
object happens to be slightly more popular than another at just the
right point, it will tend to become more popular still. As a result,
even tiny, random fluctuations can blow up, generating potentially
enormous long-run differences among even indistinguishable competitors
– a phenomenon that is similar in some ways to the famous “butterfly
effect” from chaos theory. Thus, if history were to be somehow rerun
many times, seemingly identical universes with the same set of
competitors and the same overall market tastes would quickly generate
different winners: Madonna would have been popular in this world, but
in some other version of history, she would be a nobody, and someone
we have never heard of would be in her place.
…Fortunately, the explosive growth of the Internet has made it
possible to study human activity in a controlled manner for thousands
or even millions of people at the same time. Recently, my
collaborators, Matthew Salganik and Peter Dodds, and I conducted just
such a Web-based experiment. In our study, published last year in
Science, more than 14,000 participants registered at our Web site,
Music Lab (www.musiclab.columbia.edu), and were asked to listen to,
rate and, if they chose, download songs by bands they had never heard
of. Some of the participants saw only the names of the songs and
bands, while others also saw how many times the songs had been
downloaded by previous participants. This second group — in what we
called the “social influence” condition — was further split into
eight parallel “worlds” such that participants could see the prior
downloads of people only in their own world. We didn’t manipulate any
of these rankings — all the artists in all the worlds started out
identically, with zero downloads — but because the different worlds
were kept separate, they subsequently evolved independently of one
another.
This setup let us test the possibility of prediction in two very
direct ways. First, if people know what they like regardless of what
they think other people like, the most successful songs should draw
about the same amount of the total market share in both the
independent and social-influence conditions — that is, hits shouldn’t
be any bigger just because the people downloading them know what other
people downloaded. And second, the very same songs — the “best” ones
– should become hits in all social-influence worlds.
What we found, however, was exactly the opposite…
…Social influence played as large a role in determining the market
share of successful songs as differences in quality. It’s a simple
result to state, but it has a surprisingly deep consequence. Because
the long-run success of a song depends so sensitively on the decisions
of a few early-arriving individuals, whose choices are subsequently
amplified and eventually locked in by the cumulative-advantage
process, and because the particular individuals who play this
important role are chosen randomly and may make different decisions
from one moment to the next, the resulting unpredictability is
inherent to the nature of the market. It cannot be eliminated either
by accumulating more information — about people or songs — or by
developing fancier prediction algorithms, any more than you can
repeatedly roll sixes no matter how carefully you try to throw the
die.
…Economists like Brian Arthur and Paul David have long argued that
similar mechanisms affect the competition between technologies (like
operating systems or fax machines) that display what are called
“network effects,” meaning that the attractiveness of a technology
increases with the number of people using it. But even in markets that
don’t exhibit obvious network effects (like markets for low-carb or
organically produced food, fuel-efficient vehicles or alternative
energy technologies), sudden shifts in consumer demand can still
arise, persist and then shift again. These shifts often come as
surprises but are soon explained away as mere reflections of changing
public sentiments. Yet while in some sense these markets do reflect
what people want, that is true only of what they want right now. If
markets not only reveal our preferences but also modify them, then the
relation between what we want now and what we wanted before — or what
we will want in the future — becomes deeply ambiguous.
…Just because we now know that something happened doesn’t imply that
we could have known it was going to happen at the time, even in
principle, because at the time, it wasn’t necessarily going to happen
at all.
That doesn’t mean we should stop trying to anticipate the future, any
more than we should stop trying to make sense of the past. But it does
mean that we should treat both the predictions and the explanations we
are served — whether about the next hit single, the next great
company or even the next war — with the skepticism they deserve.
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