Systems and methods for crowdsourced application advisory
The disclosed computer-implemented method for crowd sourced application advisory may include determining at least one characteristic associated with an application, collecting, from a plurality of computing devices, a sentiment associated with the application, wherein the sentiment reflects an assessment of the application in light of the at least one characteristic by at least one user of the application, presenting, via a user interface, the at least one characteristic associated with the application, the presentation of the at least one characteristic being modified by the sentiment collected from the plurality of computing devices, and receiving, via the user interface, at least one of a decision to install the application or a decision to uninstall the application. Various other methods, systems, and computer-readable media are also disclosed.
1. A computer-implemented method, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising:
analyzing a behavior of an application based on a characteristic of the application;
generating initial data for the characteristic of the application based on the analysis;
collecting, from each of a plurality of computing devices that run the application, respective data for the characteristic of the application based on an assessment of the application in light of the characteristic of the application;
modifying the initial data for the characteristic based on the collected data for the characteristic;
displaying, on a display device of the computing device, a user interface comprising an advisory for the application that includes the modified initial data for the characteristic of the application;
receiving, via the user interface, at least one of a decision to install the application or a decision to uninstall the application on the computing device based on the advisory for the application; and
based on determining that the data collected for the characteristic of the application is from at least a threshold number of computing devices and that data collected for the characteristic of another application is from less than the threshold number of computing devices, proportionally distributing the characteristic of the application to the characteristic of the other application comprising:
assigning a first weight to the characteristic in association with the application reflective of the decision to install the application or to uninstall the application; and
adjusting a second weight assigned to the characteristic in association with the other application using the first weight, the second weight for use in displaying another advisory for the other application.
2. The computer-implemented method of claim 1 , wherein the data for the characteristic of the application includes data indicating whether the application was installed on the plurality of computing devices.
3. The computer-implemented method of claim 2 , further comprising:
determining that a user of the application installed the application based on the characteristic of the application; and
updating the data for the characteristic of the application based on determining that the user of the application installed the application.
4. The computer-implemented method of claim 3 , further comprising:
collecting, from each of the plurality of computing devices that run the application, the data for the characteristic of the application that the application installation is based on.
5. The computer-implemented method of claim 3 , further comprising:
determining a degree to which the data for the characteristic of the application influences the application installation.
6. The computer-implemented method of claim 1 , wherein:
the data for the characteristic of the application is collected from each of the plurality of computing devices during a set recent time period; and
the data for the characteristic of the application reflects an assessment of the application during the set recent time period.
7. The computer-implemented method of claim 1 , wherein the characteristic of the application comprises at least one of a battery current consumption, a network data usage, a frequency of advertisement presentation, a frequency of pop-up windows, a memory storage usage, and a level of data privacy.
8. The computer-implemented method of claim 1 , wherein the assessment of the application in light of the characteristic of the application is measured by a ratio of a number of users of the plurality of computing devices that have installed the application to a number of users of the plurality of computing devices that have not installed the application.
9. A system for crowd sourced application advisory, the system comprising:
at least one physical processor; and
physical memory comprising computer-executable instructions that, when executed by the physical processor, cause the physical processor to:
analyze a behavior of an application based on a characteristic of the application;
generate initial data for the characteristic of the application based on the analysis;
collect, from each of a plurality of computing devices that run the application, respective data for the characteristic of the application based on an assessment of the application in light of the characteristic of the application;
modify the initial data for the characteristic based on the collected data for the characteristic;
display, on a display device of the computing device, a user interface comprising an advisory for the application that includes the modified initial data for the characteristic of the application;
receive, via the user interface, at least one of a decision to install the application or a decision to uninstall the application on the computing device based on the advisory for the application; and
based on determining that the data collected for the characteristic of the application is from at least a threshold number of computing devices and that data collected for the characteristic of another application is from less than the threshold number of computing devices, proportionally distribute the characteristic of the application to the characteristic of the other application comprising:
assigning a first weight to the characteristic in association with the application reflective of the decision to install the application or to uninstall the application; and
adjusting a second weight assigned to the characteristic in association with the other application using the first weight, the second weight for use in displaying another advisory for the other application.
10. The system of claim 9 , wherein the data for the characteristic of the application includes data indicating whether the application was installed on the plurality of computing devices.
11. The system of claim 10 , further comprising:
determining that the user of the application installed the application, wherein the user of the application installed the application based on the characteristic of the application; and
updating the data for the characteristic of the application based on determining that the user of the application installed the application.
12. The system of claim 11 , further comprising:
collecting, from each of the plurality of computing devices that run the application, the data for the characteristic of the application that the application installation is based on.
13. The system of claim 11 , further comprising:
determining a degree to which the data for the characteristic of the application influences the application installation.
14. The system of claim 9 , wherein:
the data for the characteristic of the application is collected from each of the plurality of computing devices during a set recent time period; and
the data for the characteristic of the application reflects an assessment of the application during the set recent time period.
15. The system of claim 9 , wherein the characteristic of the application comprises at least one of a battery current consumption, a network data usage, a frequency of advertisement presentation, a frequency of pop-up windows, a memory storage usage, and a level of data privacy.
16. A non-transitory computer-readable medium comprising one or more computer-executable instructions that, when executed by at least one processor of a computing device, cause the computing device to:
analyze a behavior of an application based on a characteristic of the application;
generate initial data for the characteristic of the application based on the analysis;
collect, from each of a plurality of computing devices that run the application, respective data for the characteristic of the application based on an assessment of the application in light of the characteristic of the application;
modify the initial data for the characteristic based on the collected data for the characteristic;
display, on a display device of the computing device, a user interface comprising an advisory for the application that includes the modified initial data for the characteristic of the application;
receive, via the user interface, at least one of a decision to install the application or a decision to uninstall the application on the computing device based on the advisory for the application; and
based on determining that the data collected for the characteristic of the application is from at least a threshold number of computing devices and that data collected for the characteristic of another application is from less than the threshold number of computing devices, proportionally distribute the characteristic of the application to the characteristic of the other application comprising:
assigning a first weight to the characteristic in association with the application reflective of the decision to install the application or to uninstall the application; and
adjusting a second weight assigned to the characteristic in association with the other application using the first weight, the second weight for use in displaying another advisory for the other application.
17. The non-transitory computer-readable medium of claim 16 , wherein the data for the characteristic of the application includes data indicating whether the application was installed on the plurality of computing devices.
18. The non-transitory computer-readable medium of claim 17 , further comprising:
determining that a user of the application installed the application based on the characteristic of the application; and
updating the data for the characteristic of the application based on determining that the user of the application installed the application.
19. The non-transitory computer-readable medium of claim 18 , further comprising:
collecting, from each of the plurality of computing devices that run the application, the data for the characteristic of the application that the application installation is based on.
20. The non-transitory computer-readable medium of claim 18 , further comprising:
determining a degree to which the data for the characteristic of the application influences the application installation.