SYSTEM FOR USER PSYCHOSOCIAL PROFILING

1 . A profiling unit comprising:

a statistical module arranged to receive user activity data and derive therefrom a plurality of statistical data that characterize the user activity data with respect to a plurality of users;

a normalization module arranged to normalize the statistical data related to each user with respect to at least one user population; and

an analysis unit arranged to analyze a correspondence between a plurality of normalized user study data and a plurality of user archetypes, and to associate, for each user, the normalized statistical data with one of the user archetypes according to the analyzed correspondence,

wherein the correspondence analysis is carried out by applying a heuristic genetic algorithm on an artificial neural network that represents the relation between the normalized user study data and the user archetypes, and

wherein the profiling unit is at least partially implemented in computer hardware.

2 . The profiling unit of claim 1 , wherein the analysis unit comprises:

a modeller arranged to represent the normalized statistical data as the artificial neural network;

a profiling module arranged to apply the heuristic genetic algorithm on the artificial neural network represented by the modeller; and

a trainer arranged to train the profiling module with obtained normalized user study data.

3 . The profiling unit of claim 1 , wherein the user activity data comprises at least one of: user data, user messages and user activity, related to user activity in at least one of: at least one social network and at least one internet forum or group.

4 . The profiling unit of claim 1 , wherein the at least one user population comprises at least one of: all users, users within a group that is related to each user, correspondents of each user and users similar to each user under specified rules.

5 . A profiling system comprising:

the profiling unit of claim 1 ;

an application interface to at least one social network platform arranged to obtain the user activity data therefrom and provide the obtained user activity data to the statistical module; and

a profiling interface arranged to present the association of users and user archetypes carried out by the analysis unit.

6 . A profiling method comprising:

deriving, from obtained user activity data, a plurality of statistical data that characterizes the user activity data with respect to a plurality of users;

normalizing the statistical data related to each user with respect to at least one user population;

analyzing a correspondence between a plurality of normalized user study data and a plurality of user archetypes by applying a heuristic genetic algorithm on an artificial neural network that represents the relation between the normalized user study data and the user archetypes; and

associating, for each user, the normalized statistical data with one of the user archetypes according to the analyzed correspondence,

wherein at least one of: the deriving, the normalizing, the analyzing, the applying and the associating is carried out by at least one computer processor.

7 . The method of claim 6 , further comprising training the heuristic genetic algorithm with obtained normalized user study data.

8 . The method of claim 6 , further comprising presenting the association of users and user archetypes to an application.

9 . A computer program product comprising a computer readable storage medium having computer readable program embodied therewith, the computer readable program comprising:

computer readable program configured to derive, from obtained user activity data, a plurality of statistical data that characterizes the user activity data with respect to a plurality of users;

computer readable program configured to normalize the statistical data related to each user with respect to at least one user population;

computer readable program configured to analyze a correspondence between a plurality of normalized user study data and a plurality of user archetypes by applying a heuristic genetic algorithm on an artificial neural network that represents the relation between the normalized user study data and the user archetypes; and

computer readable program configured to associate, for each user, the normalized statistical data with one of the user archetypes according to the analyzed correspondence.