Predictability and Prediction for an Experimental Cultural Market

TL;DR

This paper investigates how social influence affects the predictability of outcomes in an experimental cultural market, showing that early prediction can be enhanced despite social influence complicating dynamics.

Contribution

It introduces a simple model for an experimental music market, analyzes its predictability, and develops early-stage algorithms for predicting market winners and shares.

Findings

Social influence decreases ex ante predictability

Early prediction of market outcomes is possible and improved by the model

Algorithms successfully predict winners in experimental data

Abstract

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].