Aggregation-based methods for detection and correction of television viewership aberrations

摘要

Various of the disclosed embodiments contemplate television viewing behavior data collected from a plurality of television set top boxes by using aggregation to detect an excess or a deficit in viewership for a group of television set top boxes. In some embodiments, a group of set top boxes can be associated with a particular television service provider, cable television head-end, or data warehouse. Additionally, some embodiments can clean television viewing behavior data by detecting and correcting aberrant viewership in a time series, e.g. based on a weekly or an approximately monthly frequency. In some embodiments, the aberrant viewership can be detected by calculating a minimum expected number of viewers for a day and comparing it to the actual number of households that reported viewers for that day.

主权项

1. A computer-implemented method for detecting and correcting a viewership aberration, the method comprising:
selecting a first dataset corresponding to a first plurality of set top boxes associated with a first service provider; selecting a second dataset corresponding to a second plurality of set top boxes associated with at least a second service provider, the second service provider different from the first service provider, the second plurality of set top boxes different from the first plurality of set top boxes; aggregating the first dataset across the first plurality of set top boxes to create a first viewing data pattern for a selected period of time; aggregating the second dataset across the second plurality of set top boxes to create a second viewing data pattern for the selected period of time; identifying a deviation in the first viewing data pattern relative to the second viewing data pattern using a criterion, wherein the criterion comprises a minimum viewership threshold; and calculating a corrected viewership estimate based on the deviation.