Methods, apparatus, and systems to collect audience measurement data are disclosed. Disclosed example systems include first means for processing to collect (i) first media identification data corresponding to a first time period and (ii) second media identification data corresponding to a second time period after the first time period, the first media identification data and the second media identification data associated with a monitored location and second means for processing to develop behavior data based on the first media identification data and people meter data collected during the first time period with a people meter associated with the monitored location, the people meter to be deactivated during the second time period and identify an audience member associated with the second media identification data based on the behavior data and without access to any people meter data corresponding to the second time period.

A video library interface provides a listing of interactive videos and information associated with the videos and is dynamically updated as a user views the videos and makes decisions that affect the playback of the episodes. More specifically, an interactive video that includes different traversable video paths is provided to and interacted with by a user. Based on user interactions received during presentation of the video, different video paths within the interactive video are traversed. In addition, a video library display including a visual depiction of information associated with a plurality of videos is provided. The video library display is dynamically modified based on one or more interactions made by the user with respect to the interactive video.

The disclosure relates to a method for displaying information, device, system, electronic device, and storage medium. The method includes acquiring, user tag of a user account in response to a trigger operation on an information page, the user tag corresponding to one or more types of media files of the user account. The method includes displaying the user tag on the information page. The method includes displaying an associated user account corresponding to the user tag in response to an operation of selecting target user tag from the user tag.

Systems, methods, and non-transitory computer-readable media can collect a set of training videos as training data, wherein the set of training videos are labeled with one or more labels based on one or more video quality metrics associated with an evaluation objective. A machine learning model is trained based on the training data. A video to be evaluated is received. The video is assigned to a first video quality category of a plurality of video quality categories based on the machine learning model.

Systems and methods are described herein for generating a watch schedule and compressed series for a user for a series that is expected to become unavailable. Availability data indicating when a content series will become unavailable is received and compared to user progression habits. If the content series will become unavailable before the user will complete it, a watch schedule may be offered to the user. If the user subsequently falls behind on this watch schedule, a compressed version of the content series may be offered to the user.

Systems and methods for determining, based on recommendations provided by users that have consumed a media asset, which consumption options may be configured on a media device such that when configured enhance the user viewing experience for a specific media asset. The method includes accessing comments posted by other users that have consumed the media asset. The comments are analyzed to determine a consumption option recommendation. If the number of comments meet a threshold value, then the system either automatically configures the media device or configures the media device upon user approval with the recommended consumption option. The recommendation to configure a consumption option on the media device is made only if the recommendation is supported by the media device. The system also detects through audio and image analysis which users are consuming the media asset and accordingly configures the consumption options to their preferences.

One or more videos are presented to a user. The videos include a plurality of hidden artifacts. The videos also include advertisements. The user looks for the hidden artifacts in the videos. Whenever the user finds the hidden artifacts in one of the videos, the user selects locations in the videos that correspond to the hidden artifacts. A computing device performs different actions depending on which ones of the hidden artifacts the user is able to find. For example, the computing device can provide different rewards to the user depending on which ones of the hidden artifacts the user is able to find.

Systems and methods for efficiently loading interactive media guide data based on user history are provided. A plurality of asset descriptions associated with a first media asset is received. A second media asset related to the first media asset is identified. An asset description is selected form the plurality of asset descriptions based on user history of accessing the second media asset. Data for the first media asset is loaded. Data for the first media asset comprises the selected asset description.

Systems and methods are described for a media guidance application (e.g., implemented on a user device) that explains sports terminology to a user accessing content that corresponds to a sporting event. The media guidance application may detect terms used in the content, determine the terms are unique to the sport, and display definitions and explanations alongside the terms.

A system is provided for dynamic scheduling and channel creation based on external data. Audience-based parameters comprising demographics data, targeted audience data, device type data, and trending information that includes media items based on current trend in social network platform are received from external data source. A media item to be inserted in first media feed of first channel is determined based on a plurality of pre-encoded media content, metadata, audience-based parameters and defined parameters. The plurality of pre-encoded media content is segmented into a plurality of media segments, each corresponding to different quality level and content encryption mode. A second channel is generated from first channel based on audience-based parameters, insertion of media item, and second programming schedule. The second programming schedule is generated from modification of first programming schedule based on audience-based parameters. The media item is delivered, in viewable format, in second media feed to consumer device.