Ranking social network objects

• US 8,572,094 B2
• Filed: 08/17/2007
• Issued: 10/29/2013
• Est. Priority Date: 08/17/2007
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Luo, Qingshan, Cui, Hang, Zhang, Dong, Zhang, Bo
• Primary Examiner(s): HO, BINH VAN
• Application Number:
  US12/673,764
• Publication Number:
  US 20110022602A1
• Time in Patent Office: 2,265 Days
• Field of Search: 707/748
• US Class Current: 707/748
• CPC Class Codes: G06F 16/2291 User-Defined Types; Storage management thereof
• CPC Class Codes: G06F 16/23 Updating
• 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 10/10 Office automation; Time management

Abstract

An online social networking system can be used to rank social network objects of various different object types, each according to its type. The objects may comprise types such as users, communities, blogs, blog entries, events, forums, forum topics, postings, photographs, and/or images. The product comprises code for carrying out a method that begins with receiving ranking data about social network objects that comprises data about events performed on the social network. For each social network object, a ranking function is applied to ranking data about the social network object based on its type. In addition, the recency of an event on the social network related to the social network object is evaluated, in order to calculate the score for the social network object. A relative ranking for each of the plurality of social network objects based on its score is determined, and the score and relative ranking of each of the social network objects stored.

Claims

1. A computer-implemented method for ranking a plurality of communities, each community belonging to one of a plurality of different community types, the method comprising:

storing ranking data about the communities, the ranking data comprising data about events performed in the communities relating to members and posts in the communities;

determining a score for each of the communities based on types of relationships in the community and a recency of the events related to the communities, wherein the recency is calculated by applying a scale factor based on each event occurring within a predetermined time period from when the score is determined and applying an exponential time decay function to the ranking data in order to calculate the score for the community;

determining a relative ranking for each of the communities based on the respective community'"'"'s score;

storing the score and the relative ranking of each of the communities;

identifying communities with the score exceeding a predetermined threshold; and

generating code for, when executed, displaying the communities with the score exceeding the predetermined threshold in a visually distinguishable way on a webpage associated with the social network.

2. The method of claim 1, wherein the ranking data comprise page rank data about the posts in the communities.

3. The method of claim 1, wherein the ranking data comprise page rank data about web pages associated with at least one of the communities.

4. The method of claim 1, wherein the ranking data comprise data about a number of the members in the communities.

5. The method of claim 1, wherein the ranking data comprise page rank data about web pages associated with at least one the members in the communities.

6. The method of claim 1, further comprising:

receiving a query for the communities;

generating a search result to the query comprising communities; and

generating code for, when executed, displaying the search result ordered by the relative rankings of the communities.

7. The method of claim 1, further comprising:

determining, based on the relative ranking for the communities, top-ranked communities; and

generating code for, when executed, displaying the top-ranked communities to users in a visually distinguishable way on a webpage associated with the social network.

8. The method of claim 1, wherein the ranking data comprise data about a number of views of web pages associated with the communities.

9. The method of claim 1, further comprising:

applying a label to the community;

identifying different communities having a name that matches one or more terms in the label; and

providing the community to the different communities.

10. The method of claim 1, further comprising classifying the communities with the score above a predetermined threshold in a recommended category.

11. The method of claim 1, wherein the ranking data comprise data about a number of the posts in the communities.

20. The method of claim 1, wherein the ranking data is weighted based on a length of time that the members have membership in the communities.

12. A computer program product for ranking a plurality of communities, each community belonging to one of a plurality of different community types, the computer program product comprising code encoded on a non-transitory computer-readable medium for performing the steps of:

receiving ranking data about the communities, the ranking data comprising data about events performed in the communities relating to members and posts in the communities;

determining a score for each of the communities based on types of relationships in the community and a recency of the events related to the communities, wherein the recency is calculated by applying a scale factor based on each event occurring within a predetermined time period from when the score is determined and applying an exponential time decay function to the ranking data in order to calculate the score for the community;

determining a relative ranking for each of the communities based on the respective community'"'"'s score;

storing the score and the relative ranking of each of the communities;

identifying communities with the score exceeding a predetermined threshold; and

generating code for, when executed, displaying the communities with the score exceeding the predetermined threshold in a visually distinguishable way on a webpage associated with the social network.

13. The computer program product of claim 12, wherein the ranking data comprise page rank data about the posts in the communities.

14. The computer program product of claim 12, wherein the ranking data comprise page rank data about web pages associated with at least one of the communities.

15. The computer program product of claim 12, wherein the ranking data comprise data about a number of the members in the communities.

16. The computer program product of claim 12, wherein the ranking data comprise page rank data about web pages associated with at least one the members in the communities.

17. The computer program product of claim 12, wherein the steps further comprise:

receiving a query for the communities;

generating a search result to the query comprising communities of the different community types; and

generating code for, when executed, displaying the search result ordered by the relative rankings of the communities.

18. The computer program product of claim 12, wherein the steps further comprise:

determining, based on the relative ranking for the communities, top-ranked communities; and

generating code for, when executed, displaying the top-ranked communities to users in a visually distinguishable way on a webpage associated with the social network.

19. The computer program product of claim 12, wherein the ranking data comprise a number of views of web pages associated with the communities.

21. A system comprising:

a processor;

a memory storing instructions that, when executed by the processor, cause the system to;

store ranking data about the communities, the ranking data comprising data about events performed in the communities relating to members and posts in the communities;

determine a score for each of the communities based on types of relationships in the community and a recency of the events related to the communities, wherein the recency is calculated by applying a scale factor based on each event occurring within a predetermined time period from when the score is determined and applying an exponential time decay function to the ranking data in order to calculate the score for the community;

determine a relative ranking for each of the communities based on the respective community'"'"'s score;

store the score and the relative ranking of each of the communities;

identify communities with the score exceeding a predetermined threshold; and

generate code for, when executed, displaying the communities with the score exceeding the predetermined threshold in a visually distinguishable way on a webpage associated with the social network.

22. The system of claim 21, wherein the ranking data comprise page rank data about the posts in the communities.

23. The system of claim 21, wherein the ranking data comprise page rank data about web pages associated with at least one of the communities.

24. The system of claim 21, wherein the ranking data comprise data about a number of the members in the communities.