Systems and methods for measuring time spent associated with a social networking system
Systems, methods, and non-transitory computer readable media can obtain a first event stream including one or more events of a first type, where each event of the first type is associated with a timestamp. A second event stream including one or more events of a second type can be obtained, where each event of the second type is associated with a timestamp. The first event stream and the second event stream can be merged to generate information associated with a metric relating to a system, based on the timestamps associated with the one or more events of the first type and the timestamps associated with the one or more events of the second type.
1. A computer-implemented method comprising:
obtaining, by a computing system, a first event stream including two or more events of a first type, each event of the first type associated with a timestamp;
obtaining, by the computing system, a second event stream including two or more events of a second type, each event of the second type associated with a timestamp;
determining, by the computing system, an active interval cluster based on the timestamps of the two or more events of the first type; and
merging, by the computing system, the first event stream and the second event stream, during the active interval cluster, to generate information associated with a metric relating to a system, based on the timestamps associated with the two or more events of the first type and the timestamps associated with the two or more events of the second type, wherein the system is a social networking system and the metric is an amount of time spent by a user of the social networking system on an application.
2. The computer-implemented method of claim 1 , wherein each of the two or more events of the first type relates to a user activity and each of the two or more events of the second type relates to a user navigation associated with the application.
3. The computer-implemented method of claim 1 , wherein the determining the active interval cluster comprises determining whether an interval between two events of the two or more events of the first type indicated by the timestamps of the two events exceeds a threshold value.
4. The computer-implemented method of claim 1 , further comprising attributing the active interval cluster to one or more parts of the application indicated by the two or more events of the second type.
5. The computer-implemented method of claim 4 , wherein each of the two or more events of the second type indicates a transition from a first part of the application to a second part of the application, and the attributing the active interval cluster is based on the transitions indicated by the two or more events of the second type.
6. The computer-implemented method of claim 4 , further comprising obtaining a third event stream including two or more events of a third type, wherein each event of the third type is associated with at least one timestamp and relates to a functionality that is external to the application.
7. The computer-implemented method of claim 6 , further comprising adding an interval associated with an event of the two or more events of the third type to the active interval cluster.
8. The computer-implemented method of claim 1 , wherein the information associated with the metric is generated in or near real time.
9. A system comprising:
at least one hardware processor; and
a memory storing instructions that, when executed by the at least one processor, cause the system to perform:
obtaining a first event stream including two or more events of a first type, each event of the first type associated with a timestamp;
obtaining a second event stream including two or more events of a second type, each event of the second type associated with a timestamp;
determining an active interval cluster based on the timestamps of the two or more events of the first type; and
merging the first event stream and the second event stream, during the active interval cluster, to generate information associated with a metric relating to a system, based on the timestamps associated with the two or more events of the first type and the timestamps associated with the two or more events of the second type, wherein the system is a social networking system and the metric is an amount of time spent by a user of the social networking system on an application.
10. The system of claim 9 , wherein each of the two or more events of the first type relates to a user activity and each of the two or more events of the second type relates to a user navigation associated with the application.
11. The system of claim 9 , wherein the instructions further cause the system to perform attributing the active interval cluster to one or more parts of the application indicated by the two or more events of the second type.
12. A non-transitory computer readable medium including instructions that, when executed by at least one hardware processor of a computing system, cause the computing system to perform a method comprising:
obtaining a first event stream including two or more events of a first type, each event of the first type associated with a timestamp;
obtaining a second event stream including two or more events of a second type, each event of the second type associated with a timestamp;
determining an active interval cluster based on the timestamps of the two or more events of the first type; and
merging the first event stream and the second event stream, during the active interval cluster, to generate information associated with a metric relating to a system, based on the timestamps associated with the two or more events of the first type and the timestamps associated with the two or more events of the second type, wherein the system is a social networking system and the metric is an amount of time spent by a user of the social networking system on an application.
13. The non-transitory computer readable medium of claim 12 , wherein each of the two or more events of the first type relates to a user activity and each of the two or more events of the second type relates to a user navigation associated with the application.
14. The non-transitory computer readable medium of claim 12 , wherein the method further comprises attributing the active interval cluster to one or more parts of the application indicated by the two or more events of the second type.