  Individuals are often influenced by the behavior of others, for instance
because they wish to obtain the benefits of coordinated actions or infer
otherwise inaccessible information. In such situations this social influence
decreases the ex ante predictability of the ensuing social dynamics. We claim
that, interestingly, these same social forces can increase the extent to which
the outcome of a social process can be predicted very early in the process.
This paper explores this claim through a theoretical and empirical analysis of
the experimental music market described and analyzed in [1]. We propose a very
simple model for this music market, assess the predictability of market
outcomes through formal analysis of the model, and use insights derived through
this analysis to develop algorithms for predicting market share winners, and
their ultimate market shares, in the very early stages of the market. The
utility of these predictive algorithms is illustrated through analysis of the
experimental music market data sets [2].
