INFERRING USER PROFILE ATTRIBUTES FROM SOCIAL INFORMATION

• US 20120110071A1
• Filed: 10/29/2010
• Published: 05/03/2012
• Est. Priority Date: 10/29/2010
• Status: Active Grant

• Current Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Original Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Inventors: Zhou, Ding, Moreels, Pierre
• Granted Patent: US 8,495,143 B2
• Time in Patent Office: Days
• US Class Current: 709/204
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: G06Q 10/06398 Performance of employee with respect to a job function
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

User profile information for a user of a social networking system is inferred based on information about user profile of the user'"'"'s connections in the social networking system. The inferred user profile attributes may include age, gender, education, affiliations, location, and the like. To infer a value of a user profile attribute, the system may determine an aggregate value based on the attributes of the user'"'"'s connections. A confidence score may also be associated with the inferred attribute value. The set of connections analyzed to infer a user profile attribute may depend on the attribute, the types of connections, and the interactions between the user and the connections. The inferred attribute values may be used to update the user'"'"'s profile and to determine information relevant to the user to be presented to the user (e.g., targeting advertisements to the user based on the user'"'"'s inferred attributes).

Claims

1. A computer-implemented method for inferring user profile information for a user of a social networking system, the method comprising:

receiving user profile information for a set of users in the social networking system who are connected to a selected user in the social networking system;

inferring a value of the attribute for the selected user based on information describing the set of users who are connected to the selected user in the social networking system;

storing the inferred attribute in connection with a user profile of the selected user;

determining relevant information for the selected based on the inferred user profile attribute; and

sending the relevant information to the selected user.

2. The computer-implemented method of claim 1, wherein inferring the value of an attribute for the user comprises:

determining a frequency of occurrence of each value of the attribute for the set of users; and

selecting a value with a highest frequency of occurrence as the inferred value of the attribute for the selected user.

3. The computer-implemented method of claim 1, wherein inferring the value of the attribute for the selected user comprises determining the inferred value based on frequency of occurrence of values of the attribute of the set of users.

4. The computer-implemented method of claim 1, wherein inferring the value of the attribute for the selected user comprises determining the inferred value to be an average value of the attribute of the set of users

5. The computer-implemented method of claim 1, wherein inferring the value of the attribute for the selected user comprises determining the inferred value to be a median value of the attribute of the set of users

6. The computer-implemented method of claim 1, wherein inferring the value of the attribute for the selected user comprises determining an aggregate value by weighting the attribute for each user of the set of users based on a metric describing a closeness of the user with the selected user.

7. The computer-implemented method of claim 1, wherein inferring the value of the attribute for the selected user comprises determining an aggregate value by weighting the attribute for each user of the set of users based on a type value of a connection between the user and the selected user.

8. The computer-implemented method of claim 1, wherein the set of users is determined to be a subset of users connected to the selected user, the subset determined based on a metric describing a closeness of the user with the selected user.

9. The computer-implemented method of claim 1, wherein the set of users is determined to be a subset of users connected to the selected user, the subset determined based on a type value of a connection between the user and the selected user.

10. The computer-implemented method of claim 1, wherein the set of users connected to the user comprises a cluster of users selected by performing cluster analysis based on the values of the attribute being inferred.

11. The computer-implemented method of claim 1, wherein the set of users connected to the user is determined by excluding users determined to be related to the selected user as a family member.

12. The computer-implemented method of claim 1, wherein the set of users is determined based on the attribute being inferred for the selected user.

13. The computer-implemented method of claim 1, further comprising:

computing a confidence score for the inferred value of the attributes for the selected user, wherein the confidence score indicates a likelihood that the inferred value is accurate.

14. The computer-implemented method of claim 13, wherein the confidence score is determined based on the number of users of the set of users used for inferring an attribute value for the selected user.

15. The computer-implemented method of claim 1, wherein storing the inferred attribute comprises storing the inferred value of the attribute in addition to a user-provided value of the attribute.

16. The computer-implemented method of claim 1, wherein storing the inferred attribute of the user profile comprises:

comparing a confidence score value for the inferred attribute to a threshold value; and

responsive to the confidence score being above a threshold value, overwriting a user-provided value of the attribute with the inferred value of the attribute.

17. The computer-implemented method of claim 1, wherein the selected relevant information for the user comprises an advertisement.

18. The computer-implemented method of claim 1, wherein the selected relevant information for the user comprises a recommendation to establish a connection with another user in the social networking system.

19. The computer-implemented method of claim 1, wherein the inferred attribute is a location of the user, inferred by determining a location value with the highest frequency of occurrence in the set of users.

20. The computer-implemented method of claim 1, wherein the inferred attribute is a location of the user, and inferring the location of the selected user further comprises determining location of the user based on sessions created by the selected user with the social networking system.

21. The computer-implemented method of claim 1, wherein the inferred attribute is a location of the user, and inferring the location of the selected user further comprises determining location of the user based on internet protocol (IP) address of the client device used by the selected user to create sessions with the social networking system.

22. The computer-implemented method of claim 1, wherein the inferred attribute is a gender of the user, inferred by determining a gender value with the highest frequency of occurrence in the set of users.

23. The computer-implemented method of claim 1, wherein the inferred attribute is a gender of the user inferred by determining a gender value with the highest frequency of occurrence in a photo in which the selected user is tagged along with other users.

24. The computer-implemented method of claim 1, wherein the inferred attribute is a gender of the user, and inferring the value of age of the selected user further comprises performing a lookup of a dictionary mapping names to genders.

25. The computer-implemented method of claim 1, wherein the inferred attribute is an age of the user, and inferring the value of age of the selected user further comprises analyzing products associated with the user.

26. The computer-implemented method of claim 1, wherein the inferred attribute is an age of the selected user and the set of users is determined by performing cluster analysis of users connected to the selected user based on their age values.

27. The computer-implemented method of claim 1, wherein the inferred attribute is an age of the selected user and the set of users is determined by performing cluster analysis of users connected to the selected user based on their age values.

28. The computer-implemented method of claim 1, further comprising:

determining whether the inferred value of the attribute of the selected user is consistent with at least one other user profile attribute of the user; and

responsive to determining that the inferred value is inconsistent with at least one other user profile attribute, rejecting the inferred user profile value.

29. The computer-implemented method of claim 1, wherein the inferred attribute is an age of the selected user, the method further comprising:

responsive to determining that the inferred age value is below a minimum age value based on the education of the user, rejecting the inferred age value.

30. The computer-implemented method of claim 1, wherein the inferred attribute is an education level of the user inferred from an educational organization with the highest frequency of occurrence in the set of users.

31. The computer-implemented method of claim 1, wherein the inferred attribute is a time period during which the user studied at an educational organization inferred from a time period during which at least another user from the set of users indicated studying in the educational organization.

32. The computer-implemented method of claim 1, wherein the inferred attribute is an education level of the selected user, the method further comprising:

analyzing conflicts between two or more educational organization at which the selected user is inferred to have studied based on overlapping time periods during which the user studied at the educational organizations.

33. The computer-implemented method of claim 1, wherein the inferred attribute comprises one or more interests of the user, and inferring the value of the interests of the selected user further comprises performing topic analysis of interactions of the selected user with the set of users.

34. The computer-implemented method of claim 1, wherein the inferred attribute comprises one or more interests of the user, and inferring the value of the interests of the selected user further comprises performing sentiment analysis associated with topics identified in interactions of the selected user with the set of users.

35. The computer-implemented method of claim 1, wherein the inferred attribute is a language of the user, and the set of users comprise users connected to the selected user determined to be family members of the selected user.

36. The computer-implemented method of claim 1, wherein the inferred attribute is a language of the user, and inferring the language of the selected user further comprises analyzing interactions of the selected user with the set of users in the language.

37. The computer-implemented method of claim 1, wherein the inferred attribute is a language of the user, and inferring the language of the selected user comprises analyzing the number of interactions of the selected user with the set of users in the language.

38. A computer program product for providing information describing a user of a social networking system, the computer program product comprising a non-transitory computer-readable storage medium containing user profile information of a user, the user profile information inferred from information in a social networking system using a method comprising:

receiving user profile information for a set of users in the social networking system who are connected to a selected user in the social networking system;

inferring a value of the attribute for the selected user based on information describing the set of users who are connected to the selected user in the social networking system;

storing the inferred attribute in connection with a user profile of the selected user;

determining relevant information for the selected based on the inferred user profile attribute; and

sending the relevant information to the selected user.