Abstract: Prediction models for managing viewership data are disclosed. An amount of time users are displayed content is initially obtained. The obtained amounts may be for each content distributor that distributes channels, for each of the channels with respect to which sets of content are displayed, for each of the sets that comprises content displayed during past periods, and for each of the displayed content. A set of features associated with each of the displays is obtained and a target period is selected from among the past periods. A model is used to predict an amount of time users were displayed content during the target period, for each of the sets, channels, and distributors, based on the obtained sets of features associated with the displays during the target period and on the obtained amounts for the displays during the past periods that precede the target period.

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 inventions are disclosed in the microchip manufacturing arts. Conductive pattern formation by semi-additive processes are disclosed. Further conductive patterns and methods using activated precursors are also disclosed. Aluminum laminated surfaces and methods of circuit formation therefrom are further disclosed. Circuits formed on an aluminum heat sink are also disclosed. The inventive subject mater further discloses methods of electrolytic plating by controlling surface area of an anode.

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: Prediction models for managing viewership data are disclosed. An amount of time users are displayed content is initially obtained. The obtained amounts may be for each content distributor that distributes channels, for each of the channels with respect to which sets of content are displayed, for each of the sets that comprises content displayed during past periods, and for each of the displayed content. A set of features associated with each of the displays is obtained and a target period is selected from among the past periods. A model is used to predict an amount of time users were displayed content during the target period, for each of the sets, channels, and distributors, based on the obtained sets of features associated with the displays during the target period and on the obtained amounts for the displays during the past periods that precede the target period.

Abstract: A system and method to analyze the effectiveness of advertisements of presented content. The advertisements include advertisements for which the behavior desired by the advertiser is to drive a viewer to perform a certain action, such as to watch particular television program content. The system determines if an advertisement is effective by correlating exposure to presented advertisements with the subsequent presentation of content that was promoted in the advertisements. To perform the analysis, the system collects tune data from set top boxes, digital video recorders (DVRs), or other component capable of storing tune data related to the content presented on an associated display component.

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: A computer system may include at least one processor and at least one memory storing instructions that, when executed, cause the at least one processor to perform a process. The process may include receiving audio data from a user device, and accessing content data including at least one audio signature associated with video content. The process may also include correlating the audio data with the at least one audio signature and identifying recognized video content based on the correlation of the audio data with the at least one audio. The process may also include receiving tuning data including content being presented on a display component. The process may further include correlating the recognized video content with the tuning data, determining viewed video content based on the correlation of the recognized video content with the tuning data, and storing the viewed video content in a user array.

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 computer system may include at least one processor and at least one memory storing instructions that, when executed, cause the at least one processor to perform a process. The process may include receiving audio data from a user device, and accessing content data including at least one audio signature associated with video content. The process may also include correlating the audio data with the at least one audio signature and identifying recognized video content based on the correlation of the audio data with the at least one audio. The process may also include receiving tuning data including content being presented on a display component. The process may further include correlating the recognized video content with the tuning data, determining viewed video content based on the correlation of the recognized video content with the tuning data, and storing the viewed video content in a user array.

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: Various of the disclosed embodiments contemplate television viewing behavior data collected from a plurality of television set top boxes by using aggregation to detect an excess or a deficit in viewership for a group of television set top boxes. In some embodiments, a group of set top boxes can be associated with a particular television service provider, cable television head-end, or data warehouse. Additionally, some embodiments can clean television viewing behavior data by detecting and correcting aberrant viewership in a time series, e.g. based on a weekly or an approximately monthly frequency. In some embodiments, the aberrant viewership can be detected by calculating a minimum expected number of viewers for a day and comparing it to the actual number of households that reported viewers for that day.