Location-Based Content Promotion on Online Social Networks

• US 20150304437A1
• Filed: 07/03/2014
• Published: 10/22/2015
• Est. Priority Date: 04/16/2014
• Status: Active Grant

• Current Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Original Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Inventors: Vaccari, Andrea, Jia, Yuntao, Ge, Jun, Moreels, Pierre
• Granted Patent: US 9,910,479 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 1/3209 Monitoring remote activity, e.g. over telephone lines or network connections
• CPC Class Codes: G06F 1/3215 Monitoring of peripheral devices
• CPC Class Codes: G06F 16/18 File system types
• CPC Class Codes: G06F 16/24553 of query operations
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/28 Databases characterised by their database models, e.g. relational or object models
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06F 16/387 using geographical or spatial information, e.g. location
• CPC Class Codes: G06F 16/51 Indexing; Data structures therefor; Storage structures
• CPC Class Codes: G06F 16/5866 using information manually generated, e.g. tags, keywords, comments, manually generated location and time information
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9537 Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: G06V 20/30 in albums, collections or shared content, e.g. social network photos or video
• CPC Class Codes: G06V 2201/10 Recognition assisted with metadata
• CPC Class Codes: G06V 40/172 Classification, e.g. identification
• CPC Class Codes: H04L 51/52 for supporting social networking services
• CPC Class Codes: H04L 65/403 Arrangements for multi-party communication, e.g. for conferences data switching systems for conference H04L12/18; arrangements for connecting several subscribers to a common circuit, i.e. affording conference facilities H04M3/56; television conferencing systems H04N7/15
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/10 : in which an application is distributed across nodes in the network software deployment G06F8/60; multiprogramming arrangements G06F9/46
• CPC Class Codes: H04L 67/52 : specially adapted for the location of the user terminal
• CPC Class Codes: H04L 67/535 : Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04L 67/55 : Push-based network services
• CPC Class Codes: H04W 4/023 : using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds
• CPC Class Codes: H04W 4/027 : using movement velocity, acceleration information
• CPC Class Codes: H04W 4/029 : Location-based management or tracking services
• CPC Class Codes: H04W 4/08 : User group management
• CPC Class Codes: H04W 4/14 : Short messaging services, e.g. short message services [SMS] or unstructured supplementary service data [USSD]
• CPC Class Codes: H04W 4/20 : Services signaling; Auxiliary data signalling, i.e. transmitting data via a non-traffic channel
• CPC Class Codes: H04W 4/21 : for social networking applications

Abstract

In one embodiment, a computing system may access a social graph of an online social network comprising a plurality of nodes and a plurality of edges connecting the nodes, where each of the edges between two of the nodes represent a single degree of separation between them, and the nodes comprise a first node corresponding to a first user of the online social network, and a plurality of second nodes corresponding to a plurality of second users associated with the online social network. The computing system may calculate a content score for each of one or more content items shared by the second users on the online social network, where each content score is based at least in part on a proximity coefficient between the first user and the content item. The computing system may send one or more of the scored content items for display to the first user.

Claims

1. A method comprising, by one or more computing systems:

accessing a social graph of an online social network comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising;

a first node corresponding to a first user of the online social network; and

a plurality of second nodes corresponding to a plurality of second users associated with the online social network;

calculating a content score for each of one or more content items shared by the second users on the online social network, wherein each content score is based at least in part on a proximity coefficient between the first user and the content item; and

sending one or more of the content items for display to the first user based at least in part on the calculated content scores.

2. The method of claim 1, wherein the content item comprises a text, an image, a video, an audio recording, a status update, a wall post, or a message.

3. The method of claim 1, wherein the proximity coefficient is based on a location history associated with the first user and stored by the online social network, wherein the location history comprises:

one or more geographic location; and

one or more time stamps corresponding to each of the geographic locations; and

a location associated with the content item.

4. The method of claim 3, wherein the proximity coefficient is based on a time decay factor.

5. The method of claim 3, wherein the proximity coefficient is based on a determination of whether the location history comprises a geographic location within a threshold distance of the location associated with the content item.

6. The method of claim 5, wherein the geographic location comprises:

a home location of the first user;

a workplace location of the first user;

a school of the first user;

or

a location that the first user frequents.

7. The method of claim 5, wherein the location associated with the content item comprises a location history of one or more second users associated with the content item.

8. The method of claim 7, wherein the one or more second users are tagged in the content item.

9. The method of claim 7, wherein the second users have uploaded the content item to the online social network.

10. The method of claim 7, wherein the proximity coefficient calculated for a particular content item associated with a particular second user is also used for one or more additional content items associated with the particular second user.

11. The method of claim 5, wherein the proximity coefficient is based on:

the distance between the geographic location and the location associated with the content item; and

a time during which the first user was at the geographic location.

12. The method of claim 11, wherein the proximity coefficient is adjusted based on a determination of whether the first user is traveling.

13. The method of claim 12, determining whether the first user is traveling is based at least in part on the distance between a current location of the first user and a location determined to be the first user'"'"'s home.

14. The method of claim 12, wherein a proximity coefficient may be calculated based on the distance between the geographic location and the location associated with the content item without the time the first user was at the geographic location if the first user is traveling.

15. The method of claim 1, wherein calculating the content score is further based on an affinity coefficient between the first user and the content item.

16. The method of claim 15, wherein the affinity coefficient is based at least in part on a degree of separation between the first node corresponding to the first user and the concept node corresponding to the content item.

17. The method of claim 1, wherein calculating the content score comprises, for each content item:

calculating a affinity coefficient between the first user and the content item; and

calculating a proximity coefficient between the first user and the content item.

18. The method of claim 1, wherein the content items are sent for display to the first user within a newsfeed of the first user.

19. One or more computer-readable non-transitory storage media embodying software that is operable when executed to:

access a social graph of an online social network comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising;

a first node corresponding to a first user of the online social network; and

a plurality of second nodes corresponding to a plurality of second users associated with the online social network;

calculate a content score for each of one or more content items shared by the second users on the online social network, wherein each content score is based at least in part on a proximity coefficient between the first user and the content item; and

send one or more of the content items for display to the first user based at least in part on the calculated content scores.

20. A system comprising:

one or more processors; and

a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to;

access a social graph of an online social network comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising;

a first node corresponding to a first user of the online social network; and

a plurality of second nodes corresponding to a plurality of second users associated with the online social network;

calculate a content score for each of one or more content items shared by the second users on the online social network, wherein each content score is based at least in part on a proximity coefficient between the first user and the content item; and

send one or more of the content items for display to the first user based at least in part on the calculated content scores.