Abstract: Techniques are provided for displaying information about entities in a social network. An analysis of profiles of multiple representatives is performed. Each representative is registered with a social network provider and represents an organization from multiple organizations. Based on the analysis, the organizations are ranked. Data about a subset of the organizations is presented, based on the ranking, through a user interface. A user selects an indicator that is associated with a particular organization of the multiple organizations. In response to the input, a subset of the representatives is identified. One or more scores that were generated for a particular representative in the subset are determined. Data about the subset of the representatives is caused to be presented through the user interface. The data identifies the one or more scores and associates the one or more scores with the particular representative.

Abstract: 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.