Audience engagement is analyzed by receiving at least one analysis parameter comprising a content selection parameter, identifying one or more content based on the content selection parameter, determining viewership for the one or more content, determining one or more keywords for the one or more content based on the content, filtering social media messages based on the determined one or more keywords, and calculating an audience engagement measurement corresponding to the one or more content based on the viewership and the social media messages.

A server receives, from a broadcast station, a message including a station identifier and a list of media-works scheduled for broadcast. The media-works are identified by identifying attributes. The server attempts a first-level match between identifying attributes associated with a first media-work and unique identifiers included in a database. The unique identifiers link content attributes of different media-works to different unique identifiers. The first-level match includes comparing the identifying attributes to the unique identifiers to determine whether an identifying attribute matches any of the unique identifiers stored in the database. If not, a second-level match compares the identifying attributes to content attributes of different media-works to identify content attributes that match the identifying attributes. If the second-level match identifies matching content attributes that link the media-work to a unique identifiers in the database, enhanced content is selected based on that unique identifier, and is delivered to the broadcast station.

A server receives, from a broadcast station, a message including a station identifier and a list of media-works scheduled for broadcast. The media-works are identified by identifying attributes. The server attempts a first-level match between identifying attributes associated with a first media-work and unique identifiers included in a database. The unique identifiers link content attributes of different media-works to different unique identifiers. The first-level match includes comparing the identifying attributes to the unique identifiers to determine whether an identifying attribute matches any of the unique identifiers stored in the database. If not, a second-level match compares the identifying attributes to content attributes of different media-works to identify content attributes that match the identifying attributes. If the second-level match identifies matching content attributes that link the media-work to a unique identifiers in the database, enhanced content is selected based on that unique identifier, and is delivered to the broadcast station.

A computer-implemented method of using video program viewer interaction data that has been loaded to a media measurement database as input to a measurement engine which then calculates Linear, DVR, and VOD asset viewing activity at three levels: (a) Video Program, (b) Video Program Airing, (c) Video Program Airing Segment, where each level provides summary metrics for groupings of Demographic, Geographic, and/or Device Characteristic, and also second-by-second viewing metrics, including counting advertising impressions, within the Demographic, Geographic, Device groupings. System also accounts for reduced value of ad viewing when viewer is using trick plays or when viewer delays viewing recorded content. Together these metrics provide detailed information on customer viewing behavior which can be used to drive business decisions for service providers, advertisers and content producers. Additionally, a viewing histogram analysis is produced.

A computer-implemented method of using video program viewer interaction data that has been loaded to a media measurement database as input to a measurement engine which then calculates Linear, DVR, and VOD asset viewing activity at three levels: (a) Video Program, (b) Video Program Airing, (c) Video Program Airing Segment, where each level provides summary metrics for groupings of Demographic, Geographic, and/or Device Characteristic, and also second-by-second viewing metrics, including counting advertising impressions, within the Demographic, Geographic, Device groupings. System also accounts for reduced value of ad viewing when viewer is using trick plays or when viewer delays viewing recorded content. Together these metrics provide detailed information on customer viewing behavior which can be used to drive business decisions for service providers, advertisers and content producers. Additionally, a viewing histogram analysis is produced.

Channel identifiers in electronic program guide (EPG) data are consolidated for one or more EPG providers, and the consolidated channel identifiers are used to automatically process audience measurement data.

Methods and apparatus to estimate audience sizes and durations for media accesses are disclosed. An example apparatus at least one memory, instructions, and processor circuitry to execute the instructions to select constraint equations corresponding to one or more events, the one or more events corresponding to a first audience and a second audience, the first audience to include the second audience, and determine, based on the constraint equations and an auxiliary equation, event audience sizes corresponding to the first audience and to the one or more events.

Disclosed example audience measurement apparatus determine a first audience metric based on set-top box return path tuning data obtained from set-top boxes located in a first geographic area; determine a second audience metric from a portion of audience measurement data corresponding to a second geographic area, the portion of the audience measurement data associated with monitored sites in the second geographic area having second set-top box characteristics that correspond with first set-top box characteristics of the set-top boxes located in the first geographic area; determine ratios of (i) respective first audience metrics determined for respective demographic stratifications to (ii) corresponding second audience metrics determined for the respective demographic stratifications; and combine the ratios after multiplication with third audience metrics determined, for the respective demographic stratifications, from the audience measurement data to determine an audience exposure metric that estimates exposure to media in the first geographic area.

Disclosed example audience measurement apparatus determine a first audience metric based on set-top box return path tuning data obtained from set-top boxes located in a first geographic area; determine a second audience metric from a portion of audience measurement data corresponding to a second geographic area, the portion of the audience measurement data associated with monitored sites in the second geographic area having second set-top box characteristics that correspond with first set-top box characteristics of the set-top boxes located in the first geographic area; determine ratios of (i) respective first audience metrics determined for respective demographic stratifications to (ii) corresponding second audience metrics determined for the respective demographic stratifications; and combine the ratios after multiplication with third audience metrics determined, for the respective demographic stratifications, from the audience measurement data to determine an audience exposure metric that estimates exposure to media in the first geographic area.

A server system accesses a profile of a user of the media-providing service. The profile indicates a demographic group of the user. For each track of a plurality of tracks, the server system determines a year associated with the track. The server system selects content for the user based at least in part on an affinity of members of the demographic group, as compared to members of other demographic groups, of music from the year associated with the track. The server system provides the selected content to a client device associated with the user.