A demographics analysis trains classifier models for predicting demographic attribute values of videos and users not already having known demographics. In one embodiment, the demographics analysis system trains classifier models for predicting demographics of videos using video features such as demographics of video uploaders, textual metadata, and/or audiovisual content of videos. In one embodiment, the demographics analysis system trains classifier models for predicting demographics of users (e.g., anonymous users) using user features based on prior video viewing periods of users. For example, viewing-period based user features can include individual viewing period statistics such as total videos viewed. Further, the viewing-period based features can include distributions of values over the viewing period, such as distributions in demographic attribute values of video uploaders, and/or distributions of viewings over hours of the day, days of the week, and the like.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A computer-implemented method of generating a video classifier model, the method comprising: for a given demographic attribute value of a demographic attribute, and for each video of a digital video repository, identifying viewers of the video that have the demographic attribute value; forming a positive training set for the demographic attribute value including videos having highest percentages of viewers with the demographic attribute value; determining, for videos in the positive training set, features comprising demographic attribute values of uploaders of the videos in the positive training set; and training the video classifier model for the demographic attribute value using the determined features of the videos of the positive training set. 2. The computer-implemented method of claim 1, further comprising: for a new video for which a value of the demographic attribute is not already known, determining features comprising a demographic attribute value of an uploader of the new video; determining whether the new video has the demographic attribute value by applying the video classifier model for the demographic attribute value to the determined features. 3. The computer-implemented method of claim 1, wherein identifying viewers of the video that have the demographic attribute value comprises identifying the demographic attribute value in user profiles of the viewers. 4. The computer-implemented method of claim 1, further comprising training a video classifier model for each of a plurality of other demographic attribute values of the demographic attribute. 5. The computer-implemented method of claim 1, further comprising training a video classifier model for each of a plurality of other demographic attribute values of the demographic attribute. 6. The computer-implemented method of claim 5, further comprising: for a new video for which the values of the demographic attribute are not already known: determining features of the new video, the features comprising a demographic attribute value of an uploader of the new video; and for each value of the other demographic attribute values of the demographic attribute: obtaining a score by applying the video classifier model for the value to the determined features of the new video. 7. The computer-implemented method of claim 6, further comprising forming a demographic distribution for the demographic attribute using the obtained scores. 8. The computer-implemented method of claim 6, further comprising: sorting the scores into an order; and using the order to identify values of the demographic attribute to which the new video most strongly appeals. 9. A computer-readable storage medium storing instructions executable by a computer processor, the instructions comprising: instructions for, for a given demographic attribute value of a demographic attribute, and for each video of a digital video repository, identifying viewers of the video that have the demographic attribute value; instructions for forming a positive training set for the demographic attribute value including videos having highest percentages of viewers with the demographic attribute value; instructions for determining, for videos in the positive training set, features comprising: demographic attribute values of uploaders of the videos in the positive training set, and content features derived from audiovisual content of the videos in the positive training set; and instructions for training the video classifier model for the demographic attribute value using the determined features of the videos in the positive training set. 10. The computer-readable storage medium of claim 9, further comprising: for a new video for which a value of the demographic attribute is not already known, determining features comprising a demographic attribute value of an uploader of the new video; determining whether the new video has the demographic attribute value by applying the video classifier model for the demographic attribute value to the determined features. 11. The computer-readable storage medium of claim 9, wherein identifying viewers of the video that have the demographic attribute value comprises identifying the demographic attribute value in user profiles of the viewers. 12. The computer-readable storage medium of claim 9, further comprising training a video classifier model for each of a plurality of other demographic attribute values of the demographic attribute. 13. The computer-readable storage medium of claim 9, further comprising training a video classifier model for each of a plurality of other demographic attribute values of the demographic attribute. 14. The computer-readable storage medium of claim 13, further comprising: for a new video for which the values of the demographic attribute are not already known: determining features of the new video, the features comprising a demographic attribute value of an uploader of the new video; and for each value of the other demographic attribute values of the demographic attribute: obtaining a score by applying the video classifier model for the value to the determined features of the new video. 15. The computer-readable storage medium of claim 14, further comprising forming a demographic distribution for the demographic attribute using the obtained scores. 16. The computer-readable storage medium of claim 14, further comprising: sorting the scores into an order; and using the order to identify values of the demographic attribute to which the new video most strongly appeals. 17. A computer system comprising: a computer processor; and a computer-readable storage medium having instructions executable by the computer processor, the instructions comprising: instructions for, for a given demographic attribute value of a demographic attribute, and for each video of a digital video repository, identifying viewers of the video that have the demographic attribute value; instructions for forming a positive training set for the demographic attribute value including videos having highest percentages of viewers with the demographic attribute value; instructions for determining, for videos in the positive training set, features comprising: demographic attribute values of uploaders of the videos in the positive training set, and content features derived from audiovisual content of the videos in the positive training set; and instructions for training the video classifier model for the demographic attribute value using the determined features of the videos in the positive training set. 18. The computer-readable storage medium of claim 9, further comprising: for a new video for which a value of the demographic attribute is not already known, determining features comprising a demographic attribute value of an uploader of the new video; determining whether the new video has the demographic attribute value by applying the video classifier model for the demographic attribute value to the determined features. 19. The computer-readable storage medium of claim 9, wherein identifying viewers of the video that have the demographic attribute value comprises identifying the demographic attribute value in user profiles of the viewers. 20. The computer-readable storage medium of claim 9, further comprising training a video classifier model for each of a plurality of other demographic attribute values of the demographic attribute.