Hits and duds: Two opposite views

Are there experts who are really good at telling if a given novel, album or movie is likely to be a hit, and distinguish it from a dud? Industry insiders hope that they are good at this job [and some people are trying to write a program for doing this job; see below]. But an important random element may spoil their predictions, as Duncan Watts (Columbia sociologist and author of Six Degrees of Separation) explains using a very interesting study. Here's the bottomline of that study:

...[S]ocial influence [plays] 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.

Now, let's go to the other extreme. A while ago, Malcolm Gladwell wrote a piece about people who are trying to work out a success formula for determining if a movie will become a hit. Gladwell introduces the concept using a 'computer program' for predicting the success of popular music:

[A company called Platinum Blue] has a proprietary computer program that uses "spectral deconvolution software" to measure the mathematical relationships among all of a song's structural components: melody, harmony, beat, tempo, rhythm, octave, pitch, chord progression, cadence, sonic brilliance, frequency, and so on. On the basis of that analysis, the firm believes it can predict whether a song is likely to become a hit with eighty-per-cent accuracy.

* * *

Thanks to Tom Slee's wonderful blog for the pointer to Duncan Watts' column.