USING MACHINE LEARNING TECHNIQUES TO DETERMINE PROPENSITIES OF ENTITIES IDENTIFIED IN A SOCIAL GRAPH

Techniques are provided for determining a propensity or likelihood that a person in a social network will perform a particular action. A statistical model that is trained based on multiple features of each member in a first plurality of members of a social network is stored. The multiple features include a subset pertaining to profile information provided by the first plurality of members and stored in a plurality of profiles of the first plurality of members. For each member of a second plurality of members of the social network, multiple feature values that correspond to the plurality of features are identified, the statistical model is used to generate a score for the member. The score indicates a likelihood that the member will perform the particular action.