1. A method for predicting one or more characteristics of a selected user, comprising: obtaining a model based on a conditional multivariate normal distribution that relates social relationship information of one or more source users to characteristics of the one or more source users; obtaining social relationship information relating the selected user and each of one or more other users; and determining, using a hardware device, one or more characteristics of the selected user based on the model and the social relationship information that relates the selected user and each of the one or more other users, wherein determining the one or more characteristics comprises: multiplying an inverted m×m social relationship covariance matrix and a n×m user characteristics social relationship covariance matrix to derive a n×m combined covariance matrix, wherein the social relationship covariance matrix represents a deviation associated with pairs of typical values of the social relationship information of the one or more source users; subtracting a m×1 social relationship mean vector from a m×1 social relationship input vector to derive a social relationship difference vector, wherein the social relationship mean vector represents the characteristics of the one or more source users; multiplying the derived n×m combined covariance matrix and the social relationship difference vector to derive a user characteristic adjustment vector; and adding the user characteristic adjustment vector and a n×1 user characteristics mean vector to derive a n×1 user characteristics vector.