Popularity and cumulative advantage

This is part five in a part five series about choices. Click here for part one, two, three and four

I concluded this journey about making choices where we began –with the three dilemmas of choice:

  1. we have too many choices
  2. we really don’t know what we want
  3. our need to share with others

Because of these three dilemmas of choice above we often look for a cohesive solution that solves all three. The solution, I believe, is popularity. (When I say popular, it may not be what is popular to the masses, but rather smaller communities like our circle of friends, our church group or our family). After all, doing what is popular is safe. Popular means limiting managing choice. Popular means a chance to interact with other people.

Sure we may not follow what is popular in everything we do, but without “popular” we would have a hard time overcoming the three dilemmas of choice and we get stuck from time to time.

But how does something become popular? Quite simply (yet not so simply), popularity breads popularity. In other words, it’s a little thing called cumulative advantage or what Duncan Watts, professor of sociology at Columbia University, calls “the rich get richer” effect. Dr. Watts says, “[I]f one object happens to be slightly more popular than another at just the right point, it will tend to become more popular still.”

The following is a lengthy (but well worth the read [registration required]) experiment that Dr. Watts conducted about cumulative advantage:

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. In all the social-influence worlds, the most popular songs were much more popular (and the least popular songs were less popular) than in the independent condition. At the same time, however, the particular songs that became hits were different in different worlds, just as cumulative-advantage theory would predict. Introducing social influence into human decision making, in other words, didn’t just make the hits bigger; it also made them more unpredictable.

So does a listener’s own independent reaction to a song count for anything? In fact, intrinsic “quality”, which we measured in terms of a song’s popularity in the independent condition, did help to explain success in the social-influence condition. When we added up downloads across all eight social-influence worlds, “good” songs had higher market share, on average, than “bad” ones. But the impact of a listener’s own reactions is easily overwhelmed by his or her reactions to others. The song “Lockdown,” by 52metro, for example, ranked 26th out of 48 in quality; yet it was the No. 1 song in one social-influence world, and 40th in another. Overall, a song in the Top 5 in terms of quality had only a 50 percent chance of finishing in the Top 5 of success.

In our artificial market, therefore, 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.

This, obviously, presents challenges for producers and publishers – but it also has a more general significance for our understanding of how cultural markets work. Even if you think most people are tasteless or ignorant, it’s natural to believe that successful songs, movies, books and artists are somehow “better,” at least in the democratic sense of a competitive market, than their unsuccessful counterparts, that Norah Jones and Madonna deserve to be as successful as they are if only because “that’s what the market wanted.” What our results suggest, however, is that because what people like depends on what they think other people like, what the market “wants” at any point in time can depend very sensitively on its own history: there is no sense in which it simply “reveals” what people wanted all along. In such a world, in fact, the question “Why did X succeed?” may not have any better answer than the one given by the publisher of Lynne Truss’s surprise best seller, “Eats, Shoots & Leaves,” who, when asked to explain its success, replied that “it sold well because lots of people bought it.”

What can we learn from cumulative advantage? Is it completely random or can we influence the outcome by directing the “early-arriving individuals”? What do you think?

One Response

  1. […] Choices This is part one in a part five series about choices. Click here for part one, two, three, four and five […]

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