Systems and methods for generating consumption probability metrics
A consumption probability metric may be generated for a media asset. An aggregated forecast predicting user consumption of a media asset is received. A plurality of probabilities, each corresponding to a user of a plurality of users, is received, each indicating how likely a respective user is to consume the media asset. A weight for the plurality of users is calculated representing a ratio of the total number of users to a number of users in the plurality of users. A disaggregated forecast predicting user consumption of a media asset is determined based on the weight for the plurality of users and the plurality of probabilities. A modification factor is computed based on the aggregated forecast and the disaggregated forecast. A metric is generated that includes a plurality of user identifiers associated with the plurality of users and a plurality of modified probabilities each modified by the modification factor.
1. A method comprising:
receiving an aggregate score for a media asset representing a proportion of users of a total number of users predicted to consume the media asset;
automatically identifying a subset of users of a plurality of users, the subset of users each having a profile that matches a first characteristic associated with the media asset;
detecting, in each user profile of the subset of users, a user probability score representing a prediction that the respective user consumes the media asset, and calculating a combined probability score based on each of the user probability scores;
automatically computing a modified aggregate score based on the combined probability score and a weighting value determined according to a number of users in the plurality of users; and
generating a display of the modified aggregate score.
2. The method of claim 1 , wherein the weighting value is based on the total number of users and the number of users of the plurality.
3. The method of claim 1 , wherein the weighting value is obtained by dividing the total number of users by the number of users of the plurality.
4. The method of claim 1 , wherein the identifying of the subset of users comprises attempting to match a characteristic text with a text of the profile of each user of the plurality of users.
5. The method of claim 1 , further comprising recording, in a data structure of an electronic medium, a representation of the modified aggregate score.
6. The method of claim 1 , further comprising, before the detecting, receiving audience measurement data
comprising a user profile for each user of the plurality of users, each user profile comprising a respective user probability score.
7. The method of claim 1 , wherein the modified aggregate score is a proportion of users of a total number of users predicted to consume the media asset.
8. A non-transitory computer readable medium comprising instructions that when executed by control circuitry cause the control circuitry to:
receive an aggregate score for a media asset representing a proportion of users of a total number of users predicted to consume the media asset;
automatically identify a subset of users of a plurality of users, the subset of users each having a profile that matches a first characteristic associated with the media asset;
detect, in each user profile of the subset of users, a user probability score representing a prediction that the respective user consumes the media asset, and calculate a combined probability score based on each of the user probability scores;
automatically compute a modified aggregate score based on the combined probability score and a weighting value determined according to a number of users in the plurality of users; and
generate a display of the modified aggregate score.
9. The medium of claim 8 , wherein the weighting value is based on the total number of users and the number of users of the plurality.
10. The medium of claim 8 , wherein the weighting value is obtained by dividing the total number of users by the number of users of the plurality.
11. The medium of claim 8 , wherein the identifying of the subset of users comprises attempting to match a characteristic text with a text of the profile of each user of the plurality of users.
12. The medium of claim 8 , wherein the medium further comprises instructions that cause recording, in a data structure of an electronic medium, a representation of the modified aggregate score.
13. The medium of claim 8 , wherein the medium further comprises instructions that cause, before the detecting, to receive audience measurement data comprising a user profile for each user of the plurality of users, each user profile comprising a respective user probability score.
14. The medium of claim 8 , wherein the modified aggregate score is a proportion of users of a total number of users predicted to consume the media asset.
15. A system comprising:
input circuitry configured to receive an aggregate score for a media asset representing a proportion of users of a total number of users predicted to consume the media asset; processing circuitry configured to:
automatically identify a subset of users of a plurality of users, the subset of users each having a profile that matches a first characteristic associated with the media asset;
detect, in each user profile of the subset of users, a user probability score representing a prediction that the respective user consumes the media asset, and calculate a combined probability score based on each of the user probability scores;
automatically compute a modified aggregate score based on the combined probability score and a weighting value determined according to a number of users in the plurality of users; and
generate a display of the modified aggregate score.
16. The system of claim 15 , wherein the weighting value is based on the total number of users and the number of users of the plurality.
17. The system of claim 15 , wherein the weighting value is obtained by dividing the total number of users by the number of users of the plurality.
18. The system of claim 15 , wherein the identifying of the subset of users comprises attempting to match a characteristic text with a text of the profile of each user of the plurality of users.
19. The system of claim 15 , wherein the processing circuitry is further configured to receive, before the detecting, audience measurement data comprising a user profile for each user of the plurality of users, each user profile comprising a respective user probability score.
20. The system of claim 15 , wherein the modified aggregate score is a proportion of users of a total number of users predicted to consume the media asset.