Methods and systems for social network based content recommendations

1. A method comprising:

receiving a set of user interactions from a plurality of users, the set of user interactions performed on a set of data objects within a system;

generating a set of associations between the set of data objects based on the set of user interactions, the set of associations being distributed among a plurality of network graphs that include some or all of the set of user interactions performed on the set of data objects within the system, each network graph created for a different one of the plurality of users;

identifying a set of data object clusters indicative of the set of associations, the set of data object clusters forming a categorized global content network;

receiving a query from a first user of the plurality of users;

generating a plurality of recommendations indicative of a plurality of data objects of the set of data object clusters; and

causing presentation of at least a portion of the plurality of recommendations on a user interface of a user device.

2. The method of claim 1 , further comprising:

generating an organization for the set of data objects, the organization based on the set of associations between the set of data objects and the set of data object clusters; and

causing presentation of the portion of the plurality of recommendations based on the organization for the set of data objects.

3. The method of claim 2 , wherein the organization is generated based on a tie strength analysis of associations among data objects of the set of data objects within the set of data object clusters and a weighting applied to the organization, the weighting generated based on associations between the first user and the set of data objects.

4. The method of claim 2 , wherein the organization is generated based on a first tie strength analysis of associations among data objects of the set of data objects, a second tie strength analysis of associations among data objects of the set of data objects and a subset of users of the plurality of users, and a third tie strength analysis of the first user with the subset of users.

5. The method of claim 1 , further comprising:

generating an organization for the set of data objects, the organization based on the set of associations between the set of data objects and the set of data object clusters;

generating one or more graphical representations of the organization of the set of data objects, the one or more graphical representations representative of the organization and the set of data object clusters; and

causing presentation of the portion of the plurality of recommendations based on the one or more graphical representations.

6. The method of claim 5 , wherein causing presentation of the portion of the plurality of recommendations based on the one or more graphical representations further comprises:

distributing recommendations, associated with data objects of an object cluster, across the user interface based on weights for each data object within the object cluster.

7. The method of claim 1 , wherein the plurality of network graphs include nodes representative of at least a subset of data objects of the set of data objects and at least a subset of users of the plurality of users.

8. A system, comprising:

one or more processors; and

a non-transitory machine-readable storage medium coupled to the one or more processors, the non-transitory machine-readable storage medium including instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising:

receiving a set of user interactions from a plurality of users, the set of user interactions performed on a set of data objects within the system;

generating a set of associations between the set of data objects based on the set of user interactions, the set of associations being distributed among a plurality of network graphs that include some or all of the set of user interactions performed on the set of data objects within the system, each network graph created for a different one of the plurality of users;

identifying a set of data object clusters indicative of the set of associations, the set of data object clusters forming a categorized global content network;

receiving a query from a first user of the plurality of users;

generating a plurality of recommendations indicative of a plurality of data objects of the set of data object clusters; and

causing presentation of at least a portion of the plurality of recommendations on a user interface of a user device.

9. The system of claim 8 , wherein the operations further comprise:

generating an organization for the set of data objects, the organization based on the set of associations between the set of data objects and the set of data object clusters; and

causing presentation of the portion of the plurality of recommendations based on the organization for the set of data objects.

10. The system of claim 9 , wherein the organization is generated based on a tie strength analysis of associations among data objects of the set of data objects within the set of data object clusters and a weighting applied to the organization, the weighting generated based on associations between the first user and the set of data objects.

11. The system of claim 9 , wherein the organization is generated based on a first tie strength analysis of associations among data objects of the set of data objects, a second tie strength analysis of associations among data objects of the set of data objects and a subset of users of the plurality of users, and a third tie strength analysis of the first user with the subset of users.

12. The system of claim 8 , wherein the operations further comprise:

generating an organization for the set of data objects, the organization based on the set of associations between the set of data objects and the set of data object clusters;

generating one or more graphical representations of the organization of the set of data objects, the one or more graphical representations representative of the organization and the set of data object clusters; and

causing presentation of the portion of the plurality of recommendations based on the one or more graphical representations.

13. The system of claim 12 , wherein causing presentation of the portion of the plurality of recommendations based on the one or more graphical representations further comprises:

distributing recommendations, associated with data objects of an object cluster, across the user interface based on weights for each data object within the object cluster.

14. The system of claim 8 , wherein the plurality of network graphs include nodes representative of at least a subset of data objects of the set of data objects and at least a subset of users of the plurality of users.

15. A non-transitory machine-readable storage medium comprising processor executable instructions that, when executed by a processor of a machine, cause the machine to perform operations comprising:

receiving a set of user interactions from a plurality of users, the set of user interactions performed on a set of data objects within a system;

generating a set of associations between the set of data objects based on the set of user interactions, the set of associations being distributed among a plurality of network graphs that include some or all of the set of user interactions performed on the set of data objects within the system, each network graph created for a different one of the plurality of users;

identifying a set of data object clusters indicative of the set of associations, the set of data object clusters forming a categorized global content network;

receiving a query from a first user of the plurality of users;

generating a plurality of recommendations indicative of a plurality of data objects of the set of data object clusters; and

causing presentation of at least a portion of the plurality of recommendations on a user interface of a user device.

16. The non-transitory machine-readable storage medium of claim 15 , wherein the operations further comprise:

generating an organization for the set of data objects, the organization based on the set of associations between the set of data objects and the set of data object clusters; and

causing presentation of the portion of the plurality of recommendations based on the organization for the set of data objects.

17. The non-transitory machine-readable storage medium of claim 16 , wherein the organization is generated based on a tie strength analysis of associations among data objects of the set of data objects within the set of data object clusters and a weighting applied to the organization, the weighting generated based on associations between the first user and the set of data objects.

18. The non-transitory machine-readable storage medium of claim 16 , wherein the organization is generated based on a first tie strength analysis of associations among data objects of the set of data objects, a second tie strength analysis of associations among data objects of the set of data objects and a subset of users of the plurality of users, and a third tie strength analysis of the first user with the subset of users.

19. The non-transitory machine-readable storage medium of claim 15 , wherein the operations further comprise:

generating an organization for the set of data objects, the organization based on the set of associations between the set of data objects and the set of data object clusters;

generating one or more graphical representations of the organization of the set of data objects, the one or more graphical representations representative of the organization and the set of data object clusters; and

causing presentation of the portion of the plurality of recommendations based on the one or more graphical representations.

20. The non-transitory machine-readable storage medium of claim 19 , wherein causing presentation of the portion of the plurality of recommendations based on the one or more graphical representations further comprises:

distributing recommendations, associated with data objects of an object cluster, across the user interface based on weights for each data object within the object cluster.