Predicting regional viewership for broadcast media events

Abstract

Techniques for regional viewership predictions of broadcast events such as live broadcast professional sporting events. The techniques can make the predictions without a direct response variable such as regional viewership data for training a prediction model. Instead, in one technique, demand information for a good or service is used. From the demand information, a derivative demand for the good or service relative to a normal demand is determined. A regression framework is used to learn relationships between the derivative demand for the good or service and features of past live broadcast sporting events. This results in a matrix of feature weights. A non-parametric mixture framework is then used to find a set of feature weights that can be applied to features of future broadcast events to generate regional viewership predictions for the events.

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