Abstract: 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.

Abstract: Methods and systems are provided herein for calibrating subject data based on reference data, so that the calibrated subject data more closely represents a target population. The methods and systems include partitioning a reference data set into a plurality of reference data partitions using a data partitioning scheme, each reference data partition associated with a characteristic; and partitioning a subject data set into a plurality of subject data partitions using the data partitioning scheme, each subject data partition associated with a characteristic that corresponds to the characteristic associated with a reference data partition of the plurality of reference data partitions; identifying a variable present in the reference data set that is not present in the subject data set; and calculating a value of the variable for each reference data partition based on a rate of occurrence of the variable in each reference data partition.

Abstract: 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.

Abstract: Various embodiments disclose a system and methods for media content analysis based at least in part upon social media data. In some embodiments, a computer system may determine a viewership associated with a selected piece of televised content such as a television show or advertisement. The computer system may also identify social media data such as social media messages associated with the selected piece of televised content. The computer system may calculate an audience engagement measurement corresponding to the selected piece of televised content based upon the social media data and the viewership.

Abstract: Systems and methods for analyzing viewing behavior of users viewing video content and advertisements are provided. A system may periodically or continuously receive tune data reflecting the viewing behavior of users, analyze the viewing behavior to determine a location and time period of advertisement blocks in a viewed segment, and determine parameters reflecting a comparison between a number of viewers that viewed the advertisement blocks and a number of viewers that viewed non-advertised content. The system may also deliver a report of the analysis to advertisers, agencies, media sellers, or other parties that are interested in measuring the effectiveness of advertisements on users. The analysis by the system can be done over multiple different types of content-distribution platforms.

Abstract: Various embodiments disclose a system and methods for media content analysis based at least in part upon social media data. In some embodiments, a computer system may determine a viewership associated with a selected piece of televised content such as a television show or advertisement. The computer system may also identify social media data such as social media messages associated with the selected piece of televised content. The computer system may calculate an audience engagement measurement corresponding to the selected piece of televised content based upon the social media data and the viewership.

Abstract: Systems and methods for analyzing viewing behavior of users viewing video content and advertisements are provided. A system may periodically or continuously receive tune data reflecting the viewing behavior of users, analyze the viewing behavior to determine a location and time period of advertisement blocks in a viewed segment, and determine parameters reflecting a comparison between a number of viewers that viewed the advertisement blocks and a number of viewers that viewed non-advertised content. The system may also deliver a report of the analysis to advertisers, agencies, media sellers, or other parties that are interested in measuring the effectiveness of advertisements on users. The analysis by the system can be done over multiple different types of content-distribution platforms.

Abstract: Methods and systems are provided herein for calibrating subject data based on reference data, so that the calibrated subject data more closely represents a target population. The methods and systems include partitioning a reference data set into a plurality of reference data partitions using a data partitioning scheme, each reference data partition associated with a characteristic; and partitioning a subject data set into a plurality of subject data partitions using the data partitioning scheme, each subject data partition associated with a characteristic that corresponds to the characteristic associated with a reference data partition of the plurality of reference data partitions; identifying a variable present in the reference data set that is not present in the subject data set; and calculating a value of the variable for each reference data partition based on a rate of occurrence of the variable in each reference data partition.

Abstract: Various embodiments disclose a system and methods for media content analysis based at least in part upon social media data. In some embodiments, a computer system may identify social media messages corresponding to televised content. For example, following the uploading of a television show (or advertisement) to an Internet website, or transmission across a television network, viewers and non-viewers of the show may begin commenting upon the show. The system may correlate the number of viewers of the show with the social media messages to generate one or more metrics describing relations between the show's viewership and the show's social media effects.

Abstract: A system and method for analyzing the viewing behavior of end users that are viewing video content to determine the likely presence of one or more advertisements being viewed and to assess the viewers who stop viewing during the course of such advertisements. The system periodically or continuously receives tune data reflecting the viewing behavior of end users, analyzes the cumulative viewing behavior reflected by the received tune data, and delivers a report of the analysis to advertisers, agencies, media sellers, or other parties that are interested in measuring the effectiveness of advertisements on end users. The analysis by the system can be done over multiple different types of content-distribution platforms.

Abstract: A system and method that calibrates subject data for which a relationship to a target population is not known, so that the calibrated subject data can more accurately represent the target population. In many cases the calibration will involve the use of a differential weighting scheme applied to the data at the constituent level. The system and method allows the values of the observed variables in the subject data set to be weighted so that their incidence is equivalent to that of a reference population represented by a reference data set, even if the variables used in the reference data set to make estimates for the reference population were not collected or measured for the subject data set.

Abstract: A system and methods for estimating network subscription coverage within or across various markets. The system generates estimates of viewers that subscribe to certain network subscription packages in various geographic markets. The estimates may be organized in different fashions, such as organized by households, by income or other demographic, etc. In some embodiments, the system iteratively scales an estimated viewership count in a given market based on existing subscription data across all the markets and demographic characteristics of the various markets. The system may also redistribute estimates based on market capacity.

Abstract: A method and system for identifying tune data from set top boxes associated with televisions, video monitors, or other video playback devices that are likely powered off. In some embodiments, survival curves are constructed that predict a length of time before a video playback device is powered off after a tuning event. The survival curves are used to predict the likelihood that a video playback device is powered off. Viewership estimates made from tune data reported from set top boxes can be adjusted to take account of the video playback devices that are predicted to be powered off.

Abstract: A system and method are disclosed that measures audience engagement with a program based on the time a user spends viewing the program. A program's ability to retain viewers is referred to as the “stickiness” of the program. The viewership for a program is determined by the system and then compared to viewership of various other programs in order to assess the audience retention for the analyzed program as compared to the retention of the other programs. The system calculates a “stickiness index” for the program, which is a numerical representation of the analyzed program's stickiness as compared to the average of the other programs. The system may generate a report including the analyzed data and calculated stickiness index for advertisers, agencies, media sellers, or other parties that are interested in assessing viewership of the analyzed program.

Abstract: A method and system for identifying tune data from set top boxes associated with televisions, video monitors, or other video playback devices that are likely powered off. In some embodiments, survival curves are constructed that predict a length of time before a video playback device is powered off after a tuning event. The survival curves are used to predict the likelihood that a video playback device is powered off. Viewership estimates made from tune data reported from set top boxes can be adjusted to take account of the video playback devices that are predicted to be powered off.

Abstract: Various embodiments disclose a system and methods for media content analysis based at least in part upon social media data. In some embodiments, a computer system may identify social media messages corresponding to televised content. For example, following the uploading of a television show (or advertisement) to an Internet website, or transmission across a television network, viewers and non-viewers of the show may begin commenting upon the show. The system may correlate the number of viewers of the show with the social media messages to generate one or more metrics describing relations between the show's viewership and the show's social media effects.

Abstract: A system and method that calibrates subject data for which a relationship to a target population is not known, so that the calibrated subject data can more accurately represent the target population. In many cases the calibration will involve the use of a differential weighting scheme applied to the data at the constituent level. The system and method allows the values of the observed variables in the subject data set to be weighted so that their incidence is equivalent to that of a reference population represented by a reference data set, even if the variables used in the reference data set to make estimates for the reference population were not collected or measured for the subject data set.

Abstract: Various systems and methods for generating and augmenting viewership datasets are disclosed. In particular, some embodiments prepare the datasets for further analysis by supplementing missing information based upon available data. The system may organize viewership data from disparate formats into a unified form to facilitate analysis and projection of non-reporting device data. In some embodiments, the projections may scale existing cumulative determinations based on information regarding the presence and character of non-reporting devices in different geographic markets.

Abstract: A system and method that calibrates subject data for which a relationship to a target population is not known, so that the calibrated subject data can more accurately represent the target population. In many cases the calibration will involve the use of a differential weighting scheme applied to the data at the constituent level. The system and method allows the values of the observed variables in the subject data set to be weighted so that their incidence is equivalent to that of a reference population represented by a reference data set, even if the variables used in the reference data set to make estimates for the reference population were not collected or measured for the subject data set.

Abstract: A system and method are disclosed that measures audience engagement with a program based on the time a user spends viewing the program. A program's ability to retain viewers is referred to as the “stickiness” of the program. The viewership for a program is determined by the system and then compared to viewership of various other programs in order to assess the audience retention for the analyzed program as compared to the retention of the other programs. The system calculates a “stickiness index” for the program, which is a numerical representation of the analyzed program's stickiness as compared to the average of the other programs. The system may generate a report including the analyzed data and calculated stickiness index for advertisers, agencies, media sellers, or other parties that are interested in assessing viewership of the analyzed program.