Abstract: A utility application for a mobile device inspects data packets from other mobile applications running on the device to gather and record usage data about those applications. Since users of the utility application may not reflect the true population for which the usage data is desired, a system de-biases the data reported from the utility applications using a machine learning model to predict demographics of the users of the utility application. To determine a training data set for the model, the system requests a user to provide a desired user attribute by way of an in-app questionnaire. This enables labeling utility usage data with the demographics, which can be weighted and extrapolated to determine usage across the population as a whole.

Abstract: A utility application for a mobile device inspects data packets from other mobile applications running on the device to gather and record usage data about those applications. Since users of the utility application may not reflect the true population for which the usage data is desired, a system de-biases the data reported from the utility applications using a machine learning model to predict demographics of the users of the utility application. To determine a training data set for the model, the system requests a user to provide a desired user attribute by way of an in-app questionnaire. This enables labeling utility usage data with the demographics, which can be weighted and extrapolated to determine usage across the population as a whole.