1. A method for generating a model for predicting one or more characteristics of a selected user, comprising: obtaining a model template for predicting the one or more characteristics of the selected user, the model template including one or more parameters associated with social relationship information for the selected user; applying training data to the model template in order to develop the model, the training data comprising social relationship information and one or more user characteristics for each of one or more source users; and determining the one or more parameters based on the training data as applied to the model template, the one or more parameters including a mean vector representing the characteristics of the one or more source users and a covariance matrix for the model based on a conditional multivariate normal distribution, the covariance matrix representing a deviation associated with pairs of typical values of the social relationship information of the one or more source users, wherein the covariance matrix is determined by: determining a sum of products of a first column of the training data and a second column of the training data; dividing each some of products by a count of columns of the training data to produce a mean of products; multiplying a first mean vector of the first column by a second mean vector of the second column to produce a product of means vector; and subtracting the product of means vector from the means of products.