Inferring household income for users of a social networking system

摘要

Information about a set of users of a social networking system is obtained to develop a predictive model of income distribution for all users of the social networking system. This predictive model is based on selected attributes about the users (e.g., declared/profile information, user historical information, and/or social information). Users of the social networking system are mapped to a specific income bracket based on statistical correlations derived from the predictive model. Advertisements are targeted to users based on income bracket. The system may use a machine learning algorithm to analyze conversion rates of targeted advertising to retrain the predictive model.