RANKING INTERACTIONS BETWEEN USERS ON THE INTERNET

• US 20090217178A1
• Filed: 11/24/2008
• Published: 08/27/2009
• Est. Priority Date: 02/26/2008
• Status: Active Grant

• Current Assignee: LivingSocial Incorporated (Groupon Incorporated)
• Original Assignee: Social Media Networks Inc. (v2 Ventures Group LLC)
• Inventors: Gentzel, David, Niyogi, Sourabh
• Granted Patent: US 8,499,247 B2
• Time in Patent Office: Days
• US Class Current: 715/753
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/955 using information identifiers, e.g. uniform resource locators [URL]
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G06Q 30/00 Commerce
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute

Abstract

A system and method for determining the amount of influence users of the internet have on other users of the internet based on data from interactions between users on the internet.

Claims

1. A method performed on a computer system for ranking influence of users of the internet on other users of the internet based on interactions between the users comprising:

receiving an interaction history comprising a set of one or more interactions for a first user with a plurality of additional users;

determining an interaction score for an interaction of the set;

determining an influence rank for each of the plurality of additional users based on the interaction history; and

storing the influence rank in a storage medium for subsequent retrieval to determine content to serve on the internet.

2. The method of claim 1 further comprising storing the interaction history in a storage medium.

3. The method of claim 1 wherein determining an influence rank is based upon the interaction score.

4. The method of claim 1 wherein the interaction history comprises metadata associated with the interaction.

5. The method of claim 1 wherein determining the interaction score comprises determining a period of time between a first interaction of the set and a second interaction of the set.

6. The method of claim 1 wherein determining the interaction score comprises determining that one interaction of the set is a repetition of a second interaction of the set.

7. The method of claim 1 wherein determining an interaction score comprises determining how many users took part in the interaction.

8. The method of claim 1 wherein determining an interaction score comprises serializing the interaction.

9. The method of claim 1 wherein determining an interaction score comprises determining a type of the interaction.

10. The method of claim 1 wherein determining an interaction score comprises determining an application in which the interaction occurred.

11. The method of claim 1 wherein determining an influence rank comprises determining a percentile rank for the plurality of additional users.

12. The method of claim 1 wherein determining an influence rank comprises determining a context associated with the influence rank.

13. The method of claim 1 further comprising determining a second influence rank associated with a second context and storing the second influence rank in a storage medium for subsequent retrieval to determine content related to the second context to serve on the internet.

14. A system for ranking influence of users of the internet on other users of the internet based on interactions between users comprising:

a first database for storing an interaction history comprising a set of one or more interactions for a first user with a plurality of additional users;

an analysis engine for receiving the interaction history and determining an interaction score for an interaction of the set of the first user with the plurality of additional users and determining an influence rank for each of the plurality of additional users based on the interaction history of the first user with the plurality of additional users, and;

a second database for storing the influence rank for later retrieval to determine content to serve on the internet.

15. The system of claim 14 wherein the second database stores the interaction score for the set of the first user with the plurality of additional users.

16. A computer program product, comprising:

a computer usable medium having computer readable program code embodied therein to rank influence of users of the internet on other users of the internet based on interactions between the users, the computer readable program code in the computer program product comprising;

computer readable program code to receive an interaction history comprising a set of one or more interactions for a first user with a plurality of additional users;

computer readable program code to determine an interaction score for an interaction of the set;

computer readable program code to determine an influence rank for each of the plurality of additional users based on the interaction history; and

computer readable program code to store the influence rank in a storage medium for subsequent retrieval to determine content to serve on the internet.

17. The computer program product of claim 16 further comprising computer readable program code to store the interaction history in a storage medium.

18. The computer program product of claim 16 wherein the computer readable program code to determine an influence rank comprises computer readable program code to determine an influence rank based upon the interaction score.

19. The computer program product of claim 16 wherein the interaction history comprises metadata associated with the interaction.

20. The computer program product of claim 16 wherein the computer readable program code to determine the interaction score comprises computer readable program code to determine a period of time between a first interaction of the set and a second interaction of the set.

21. The computer program product of claim 16 wherein the computer readable program code to determine the interaction score comprises computer readable program code to determine that one interaction of the set is a repetition of a second interaction of the set.

22. The computer program product of claim 16 wherein the computer readable program code to determine an interaction score comprises computer readable program code to determine how many users took part in the interaction.

23. The computer program product of claim 16 wherein the computer readable program code to determine an interaction score comprises computer readable program code to serialize the interaction.

24. The computer program product of claim 16 wherein determining the computer readable program code to determine an interaction score comprises computer readable program code to determine a type of the interaction.

25. The computer program product of claim 16 wherein the computer readable program code to determine an interaction score comprises computer readable program code to determine an application in which the interaction occurred.

26. The computer program product of claim 16 wherein the computer readable program code to determine an influence rank comprises computer readable program code to determine a percentile rank for the plurality of additional users.

27. The computer program product of claim 16 wherein the computer readable program code to determine an influence rank comprises computer readable program code to determine a context associated with the influence rank.

28. The computer program product of claim 16 further comprising:

computer readable program code to determine a second influence rank associated with a second context; and

computer readable program code to store the second influence rank in a storage medium for subsequent retrieval to determine content related to the second context to serve on the internet.