Systems and methods for determining quality levels for videos to be uploaded
Systems, methods, and non-transitory computer-readable media can define a set of video quality levels. One or more social engagement signals associated with videos uploaded at each video quality level out of the set of video quality levels can be acquired. Information associated with each user out of a set of users can be acquired. A respective video quality level for each user can be determined based on at least one of the information associated with each user or the one or more social engagement signals.
1. A computer-implemented method comprising:
receiving, by a computing system, a request to upload a content item from a user;
determining, by the computing system, an upload cessation likelihood metric for the user; and
selecting, by the computing system, a quality level for uploading the content item based at least in part on the upload cessation likelihood metric.
2. The computer-implemented method of claim 1 , wherein the upload cessation likelihood metric is based at least in part on a file size, a resolution, a bit rate, or a codec associated with the content item.
3. The computer-implemented method of claim 1 , wherein the upload cessation likelihood metric is based at least in part on upload cessation data associated with the user.
4. The computer-implemented method of claim 3 , wherein the upload cessation data associated with the user comprises one or more of: a property of a device associated with the user, a network condition associated with the device, a user preference provided by the user, an upload cancellation associated with the user, or an upload failure associated with the user.
5. The computer-implemented method of claim 4 , wherein the property of the device associated with the user comprises one or more of: a codec capability, a manufacturer identifier, a model identifier, an operating system version, or a location.
6. The computer-implemented method of claim 4 , wherein the network condition associated with the device comprises one or more of: a network type, a network bandwidth, a network connectivity, a network availability, a network address, or a round-trip time.
7. The computer-implemented method of claim 1 , wherein selecting a quality level for uploading the content item is further based at least in part on a social engagement likelihood metric associated with the content item.
8. The computer-implemented method of claim 7 , wherein the social engagement likelihood metric is based at least in part on one or more social engagement signals associated with a plurality of uploaded content items.
9. The computer-implemented method of claim 8 , wherein the one or more social engagement signals comprise one or more of: a like operation, a share operation, a comment operation, a delete operation, or a save operation.
10. The computer-implemented method of claim 1 , wherein the upload cessation likelihood metric is associated with a confidence score indicating how likely an upload cessation will occur.
11. A system comprising:
at least one processor; and
a memory storing instructions that, when executed by the at least one processor, cause the system to perform:
receiving a request to upload a content item from a user;
determining an upload cessation likelihood metric for the user; and
selecting a quality level for uploading the content item based at least in part on the upload cessation likelihood metric.
12. The system of claim 11 , wherein the upload cessation likelihood metric is based at least in part on a file size, a resolution, a bit rate, or a codec associated with the content item.
13. The system of claim 11 , wherein the upload cessation likelihood metric is based at least in part on upload cessation data associated with the user.
14. The system of claim 13 , wherein the upload cessation data associated with the user comprises one or more of: a property of a device associated with the user, a network condition associated with the device, a user preference provided by the user, a prior upload cancellation associated with the user, or a prior upload failure associated with the user.
15. The system of claim 14 , wherein the property of the device associated with the user comprises one or more of: a codec capability, a manufacturer identifier, a model identifier, an operating system version, or a location.
16. A non-transitory computer-readable storage medium including instructions that, when executed by at least one processor of a computing system, cause the computing system to perform:
receiving a request to upload a content item from a user;
determining an upload cessation likelihood metric for the user; and
selecting a quality level for uploading the content item based at least in part on the upload cessation likelihood metric.
17. The non-transitory computer-readable storage medium of claim 16 , wherein the upload cessation likelihood metric is based at least in part on a file size, a resolution, a bit rate, or a codec associated with the content item.
18. The non-transitory computer-readable storage medium of claim 16 , wherein the upload cessation likelihood metric is based at least in part on upload cessation data associated with the user.
19. The non-transitory computer-readable storage medium of claim 18 , wherein the upload cessation data associated with the user comprises one or more of: a property of a device associated with the user, a network condition associated with the device, a user preference provided by the user, a prior upload cancellation associated with the user, or a prior upload failure associated with the user.
20. The non-transitory computer-readable storage medium of claim 19 , wherein the property of the device associated with the user comprises one or more of: a codec capability, a manufacturer identifier, a model identifier, an operating system version, or a location.