Dynamic geographic beacons for geographic-positioning-capable devices
In one embodiment, a processor may identify information about an entity represented by a first node in a social graph for a social-networking system. The information may comprise a location for the entity and an affinity score for the entity with respect to a user, wherein the user is represented by a second node in the social graph. The processor may then determine a region defined with respect to the location of the entity, wherein the region is defined based in part on the affinity score for the entity, as well as determining that a location of a mobile device associated with the user is within the region. Finally, the processor may cause the mobile device to transition from a sleep state to an active state.
1. A method comprising:
identifying, by a processor, information about an entity represented by a first node in a social graph for a social-networking system, wherein the information comprises a location for the entity and an affinity score for the entity with respect to a user, wherein the user is represented by a second node in the social graph;
determining, by the processor, that a location of a mobile device associated with the user is within a region associated with the entity, wherein a size of the region is defined based in part on the affinity score for the entity; and
executing, by the processor, a special-purpose client application on the mobile device to present, to the user, information related to the entity.
2. The method of claim 1 , wherein the first node is connected to the second node representing the user by one or more edges of the social graph, and wherein the affinity score for the entity is based in part on relevancy of the entity to the user.
3. The method of claim 2 , wherein the relevancy of the entity to the user is based on content corresponding to the entity.
4. The method of claim 1 , wherein the special-purpose client application further reports the user's current location to the social-networking system.
5. The method of claim 1 , wherein the special-purpose client application further automatically checks-in the user at the entity.
6. The method of claim 1 , wherein the size of the region is further defined based at least in part on a time of day, a power budget of the mobile device, or an error associated with the location of the entity or with the location of the mobile device.
7. The method of claim 1 , wherein the size of the region is further defined based at least in part on a velocity of the mobile device.
8. The method of claim 7 , wherein the velocity of the mobile device is determined based at least in part on the location of the mobile device or a default velocity.
9. The method of claim 1 , wherein the location of the entity or the location of the mobile device is based at least in part on:
a global positioning system (GPS) signal;
a Wi-Fi signal; or
a cellular radio signal.
10. One or more computer-readable non-transitory storage media embodying software that is operable when executed to:
identify information about an entity represented by a first node in a social graph for a social-networking system, wherein the information comprises a location for the entity and an affinity score for the entity with respect to a user, wherein the user is represented by a second node in the social graph;
determine that a location of a mobile device associated with the user is within a region associated with the entity, wherein a size of the region is defined based in part on the affinity score for the entity; and
execute a special-purpose client application on the mobile device to present, to the user, information related to the entity.
11. The media of claim 10 , wherein the first node is connected to the second node representing the user by one or more edges of the social graph, and wherein the affinity score for the entity is based in part on relevancy of the entity to the user.
12. The media of claim 11 , wherein the relevancy of the entity to the user is based on content corresponding to the entity.
13. The media of claim 10 , wherein the special-purpose client application further reports the user's current location to the social-networking system.
14. The media of claim 10 , wherein the special-purpose client application further automatically checks-in the user at the entity.
15. The media of claim 10 , wherein the size of the region is further defined based at least in part on a time of day, a power budget of the mobile device, or an error associated with the location of the entity or with the location of the mobile device.
16. The media of claim 10 , wherein the size of the region is further defined based at least in part on a velocity of the mobile device.
17. The media of claim 16 , wherein the velocity of the mobile device is determined based at least in part on the location of the mobile device or a default velocity.
18. The media of claim 17 , wherein the location of the entity or the location of the mobile device is based at least in part on:
a global positioning system (GPS) signal;
a Wi-Fi signal; or
a cellular radio signal.
19. A computing device comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors being operable when executing the instructions to:
identify information about an entity represented by a first node in a social graph for a social-networking system, wherein the information comprises a location for the entity and an affinity score for the entity with respect to a user, wherein the user is represented by a second node in the social graph;
determine that a location of a mobile device associated with the user is within a region associated with the entity, wherein a size of the region is defined based in part on the affinity score for the entity; and
execute a special-purpose client application on the mobile device to present, to the user, information related to the entity.
20. The computing device of claim 19 , wherein the first node is connected to the second node representing the user by one or more edges of the social graph, and wherein the affinity score for the entity is based in part on relevancy of the entity to the user.