Abstract: Mobile usage data representing the access of one or more resources on a network by mobile devices is accessed. The mobile usage data includes information received from mobile devices as a result of beacon instructions included with the one or more resources. A first set of data representing information about accesses to the one or more resources by mobile devices with persistent beacon cookies is determined. A second set of data representing information about accesses to the one or more resources by mobile devices with non-persistent beacon cookies is determined. One or more adjustment factors are determined based on the first set of data. A count of unique visitors accessing the one or more resources from the mobile devices is determined based on a count of accesses by the mobile devices with persistent beacon cookies and a count of accesses by the mobile devices with non-persistent beacon cookies adjusted by the one or more adjustment factors.

Abstract: Measuring a networked audience is described. Initially, a first set of network usage data based on access of a resource by a first set of client systems is received. Next, a second set of network usage data based on access of the resource by a second set of client systems using a monitoring application installed on the second set of client systems is determined. Usage of the resource based on the first set of network usage data during a time period and one or more adjustment factors based on the second set of network usage data are determined. The determined usage is adjusted using the one or more adjustment factors. Finally, one or more audience reports for the resource using the adjusted usage are generated.

Abstract: Measuring a networked audience is described. Initially, a first set of network usage data based on access of a resource by a first set of client systems is received. Next, a second set of network usage data based on access of the resource by a second set of client systems using a monitoring application installed on the second set of client systems is determined. Usage of the resource based on the first set of network usage data during a time period and one or more adjustment factors based on the second set of network usage data are determined. The determined usage is adjusted using the one or more adjustment factors. Finally, one or more audience reports for the resource using the adjusted usage are generated.

Abstract: Measuring a networked audience is described. Initially, a first set of network usage data is determined based on a first set of signaling information obtained from a first subset of the client systems as a result of the first subset accessing common resources. In addition, a second set of network usage data is determined based on a second set of information obtained from a second subset of the client systems as a result of an application installed thereon monitoring accessing of the common resources. Usage is measured based on the first set of network usage data by determining an initial count of unique visitors that accessed the common resources by determining a count related to signaling of the first set of signaling information. Adjustment factors are determined based on the second set of network usage data. Finally, audience reports are generated by adjusting the measured usage using the one or more adjustment factors.

Abstract: Mobile usage data representing the access of one or more resources on a network by mobile devices is accessed. The mobile usage data includes information received from mobile devices as a result of beacon instructions included with the one or more resources. A first set of data representing information about accesses to the one or more resources by mobile devices with persistent beacon cookies is determined. A second set of data representing information about accesses to the one or more resources by mobile devices with non-persistent beacon cookies is determined. One or more adjustment factors are determined based on the first set of data. A count of unique visitors accessing the one or more resources from the mobile devices is determined based on a count of accesses by the mobile devices with persistent beacon cookies and a count of accesses by the mobile devices with non-persistent beacon cookies adjusted by the one or more adjustment factors.

Abstract: Usage data representing the access of a network entity by a plurality of client devices each associated with one or more Internet Protocol (IP) addresses of a plurality of IP addresses is initially accessed. Then a set of static IP addresses of the plurality of IP addresses is determined based on the usage data. A first count of static IP addresses of the set of static IP addresses that are all associated with mobile traffic or that are all associated with non-mobile traffic is determined. A second count of static IP addresses of the set of static IP addresses that are associated with the mobile traffic and the non-mobile traffic is also determined. An overlap factor is determined based on a ratio between the first count of static IP addresses and the second count of static IP addresses. Based on the overlap factor, a total count of unique static IP addresses via which the network entity was accessed is finally determined.

Abstract: Measuring a networked audience is described. Initially, a first set of network usage data is determined based on a first set of signaling information obtained from a first subset of the client systems as a result of the first subset accessing common resources. In addition, a second set of network usage data is determined based on a second set of information obtained from a second subset of the client systems as a result of an application installed thereon monitoring accessing of the common resources. Usage is measured based on the first set of network usage data by determining an initial count of unique visitors that accessed the common resources by determining a count related to signaling of the first set of signaling information. Adjustment factors are determined based on the second set of network usage data. Finally, audience reports are generated by adjusting the measured usage using the one or more adjustment factors.

Abstract: A first set of usage data for a first set of resources on a network and a second set of usage data for a second set of resources on a network are accessed. The first set of resources were accessed by a first group of client systems and the first set of usage data is determined based on information received from the first group of client systems sent as a result of beacon instructions included with the first set of resources. The second set of usage data is determined based on information received from monitoring applications installed on a second group of client systems that accessed the second set of resources. Users of the second group of client systems are a sample of a larger group of users that use resources on the network. Initial usage measurement data for a third set of resources on the network is determined based on the first set of usage data. The third set includes one or more common resources that are included in the first set of resources and the second set of resources.

Abstract: Usage data representing the access of a network entity by a plurality of client devices each associated with one or more Internet Protocol (IP) addresses of a plurality of IP addresses is initially accessed. Then a set of static IP addresses of the plurality of IP addresses is determined based on the usage data. A first count of static IP addresses of the set of static IP addresses that are all associated with mobile traffic or that are all associated with non-mobile traffic is determined. A second count of static IP addresses of the set of static IP addresses that are associated with the mobile traffic and the non-mobile traffic is also determined. An overlap factor is determined based on a ratio between the first count of static IP addresses and the second count of static IP addresses. Based on the overlap factor, a total count of unique static IP addresses via which the network entity was accessed is finally determined.

Abstract: Usage data representing the access of a set of resources on a network is accessed. The usage data is based at least in part on information received from client systems sent as a result of beacon instructions included with the set of resources. First and second sets of usage data representing access by client systems classified as a first type and a second type, respectively, are determined based on the accessed usage data. Counts of unique visitors accessing the network resources from each of the first and second types of client systems, based on the first and sets of usage data, respectively, are each determined. A total count of unique visitors accessing the network resources from the first and second types of client systems is determined based on data representing the usage overlap of devices of the first type with devices of the second type.

Abstract: Tuning data representing a television viewing event associated with a particular household is accessed. Household member data representing information on individual members of the particular household is accessed. Viewing profile data representing information on individual members of other households regarding viewership by the individual members of the other households is accessed. Fractional viewership values for the individual members of the particular household are determined based on the tuning data, the household member data, and the viewing profile data. Household viewership data is determined based on the fractional viewership values.

Abstract: The present disclosure describes techniques for projecting person-level viewership from household-level tuning events. One example method includes accessing tuning data representing television tuning events associated with particular households; accessing panelist viewing data representing television viewing events associated with panelists; and for at least one tuning event represented by the tuning data: accessing household member data associated with the tuning event; determining a member minutes value associated with each individual member of the particular household for the tuning event; and determining a fractional viewership value for each individual member of the particular household associated with the tuning event.

Abstract: Panel and census data representing accesses by sets of users with multiple types of media platforms to media content associated with multiple media entities is accessed. An overlap in the accessed panel data that represents users who have accessed media content associated with the media entity with more than one of the multiple types of media platforms is determined. Based on the accessed panel data, the determined overlap in the accessed panel data, and the accessed census data, an overlap function that estimates an overlap in the accessed census data is derived. The derived overlap function is applied to census data associated with a media entity to estimate an overlap in the census data associated with the media entity. The overlap in the census data represents users who have accessed media content associated with the media entity with more than one of the multiple types of media platforms.

Abstract: A first set of usage data for a first set of resources on a network and a second set of usage data for a second set of resources on a network are accessed. The first set of resources were accessed by a first group of client systems and the first set of usage data is determined based on information received from the first group of client systems sent as a result of beacon instructions included with the first set of resources. The second set of usage data is determined based on information received from monitoring applications installed on a second group of client systems that accessed the second set of resources. Users of the second group of client systems are a sample of a larger group of users that use resources on the network. Initial usage measurement data for a third set of resources on the network is determined based on the first set of usage data. The third set includes one or more common resources that are included in the first set of resources and the second set of resources.

Abstract: Usage data representing the access of a set of resources on a network is accessed. The usage data is based at least in part on information received from client systems sent as a result of beacon instructions included with the set of resources. First and second sets of usage data representing access by client systems classified as a first type and a second type, respectively, are determined based on the accessed usage data. Counts of unique visitors accessing the network resources from each of the first and second types of client systems, based on the first and sets of usage data, respectively, are each determined. A total count of unique visitors accessing the network resources from the first and second types of client systems is determined based on data representing the usage overlap of devices of the first type with devices of the second type.

Abstract: A first set of usage data for a first set of resources on a network and a second set of usage data for a second set of resources on a network are accessed. The first set of resources were accessed by a first group of client systems and the first set of usage data is determined based on information received from the first group of client systems sent as a result of beacon instructions included with the first set of resources. The second set of usage data is determined based on information received from monitoring applications installed on a second group of client systems that accessed the second set of resources. Users of the second group of client systems are a sample of a larger group of users that use resources on the network. Initial usage measurement data for a third set of resources on the network is determined based on the first set of usage data. The third set includes one or more common resources that are included in the first set of resources and the second set of resources.

Abstract: Usage data representing the access of a set of resources on a network is accessed. The usage data is based at least in part on information received from client systems sent as a result of beacon instructions included with the set of resources. First and second sets of usage data representing access by client systems classified as a first type and a second type, respectively, are determined based on the accessed usage data. Counts of unique visitors accessing the network resources from each of the first and second types of client systems, based on the first and sets of usage data, respectively, are each determined. A total count of unique visitors accessing the network resources from the first and second types of client systems is determined based on data representing the usage overlap of devices of the first type with devices of the second type.

Abstract: The present disclosure describes techniques for projecting person-level viewership from household-level tuning events. One example method includes accessing tuning data representing television tuning events associated with particular households; accessing panelist viewing data representing television viewing events associated with panelists; and for at least one tuning event represented by the tuning data: accessing household member data associated with the tuning event; determining a member minutes value associated with each individual member of the particular household for the tuning event; and determining a fractional viewership value for each individual member of the particular household associated with the tuning event.

Abstract: Panel and census data representing accesses by sets of users with multiple types of media platforms to media content associated with multiple media entities is accessed. An overlap in the accessed panel data that represents users who have accessed media content associated with the media entity with more than one of the multiple types of media platforms is determined. Based on the accessed panel data, the determined overlap in the accessed panel data, and the accessed census data, an overlap function that estimates an overlap in the accessed census data is derived. The derived overlap function is applied to census data associated with a media entity to estimate an overlap in the census data associated with the media entity. The overlap in the census data represents users who have accessed media content associated with the media entity with more than one of the multiple types of media platforms.

Abstract: Tuning data representing a television viewing event associated with a particular household is accessed. Household member data representing information on individual members of the particular household is accessed. Viewing profile data representing information on individual members of other households regarding viewership by the individual members of the other households is accessed. Fractional viewership values for the individual members of the particular household are determined based on the tuning data, the household member data, and the viewing profile data. Household viewership data is determined based on the fractional viewership values.