Mapping user agents in network traffic data to client devices associated with a media exposure location
In one example, a method is described. The method includes: obtaining network traffic data including at least one user agent, where the user agent is associated with a client device coupled to a network at a media exposure measurement location, and where the user agent comprises a string of characters defining client device attributes, comparing one or more of the client device attributes to candidate device attributes stored in an audience measurement database, based on the comparison, selecting, from a set of candidate device attributes, a set of target device attributes corresponding to a target device identifier, determining a number of occurrences of the set of target device attributes in the network traffic data, and based on a determination that the number of occurrences is above a threshold, outputting the target device identifier as the device identifier that corresponds to the user agent.
1 . A method for mapping a user agent included in network traffic data onto a device identifier associated with a client device at a media exposure measurement location, the method comprising:
obtaining the network traffic data comprising at least one user agent, wherein the user agent is associated with the client device coupled to a network at the media exposure measurement location, and wherein the user agent comprises a string of characters defining client device attributes;
comparing two or more of the client device attributes to candidate device attributes stored in an audience measurement database, wherein the audience measurement database comprises, for each of a plurality of candidate device identifiers, a corresponding set of candidate device attributes;
based on the comparison, selecting, from a set of candidate device attributes, a set of target device attributes corresponding to a target device identifier;
determining a number of occurrences of the set of target device attributes in the network traffic data; and
based on a determination that the number of occurrences is above a threshold, outputting the target device identifier as the device identifier that corresponds to the user agent.
2 . The method of claim 1 , wherein determining the number of occurrences of the set of target device attributes comprises:
selecting a first target device attribute and a second target device attribute; and
determining a number of occurrences of a combination of the first target device attribute and the second target device attribute in the network traffic data.
3 . The method of claim 1 , wherein the client device is a mobile phone.
4 . The method of claim 1 , further comprising:
selecting one or more portions of the string of characters, each portion of the string of characters defining a respective client device attribute.
5 . The method of claim 4 , wherein the method further comprises:
providing the one or more portions of the string of characters to a validation engine, wherein the validation engine is configured to, for each of the one or more portions of the string of characters:
process the portion of the string of characters to generate an output indicating that the portion of the string of characters represents a valid client device attribute or an invalid client device attribute.
6 . The method of claim 1 , wherein the network traffic data is collected by a streaming meter that is located at the media exposure measurement location and that is communicatively coupled to the client device, and wherein the streaming meter is configured to monitor the network to collect the network traffic data.
7 . The method of claim 1 , wherein the two or more client device attributes comprise two or more of: a type of the client device, a model of the client device, a make of the client device, or an operating system associated with the client device.
8 . The method of claim 1 , wherein the set of candidate device attributes in the audience measurement database are provided by users of devices associated with the media exposure measurement location.
9 . The method of claim 1 , further comprising:
determining a confidence score for the target device identifier; and
outputting the confidence score in addition to the target device identifier that corresponds to the user agent.
10 . The method of claim 1 , wherein selecting, from the set of candidate device attributes, the set of target device attributes corresponding to the target device identifier comprises:
determining that at least some of the client device attributes defined by the user agent substantially match at least some of the candidate device attributes in the audience measurement database.
11 . A computing system comprising:
a processor; and
a non-transitory computer-readable storage medium, having stored thereon program instructions that, upon execution by the processor, cause performance of a set of operations for mapping a user agent included in network traffic data onto a device identifier associated with a client device at a media exposure measurement location, the operations comprising:
obtaining the network traffic data comprising at least one user agent, wherein the user agent is associated with the client device coupled to a network at the media exposure measurement location, and wherein the user agent comprises a string of characters defining client device attributes;
comparing two or more of the client device attributes to candidate device attributes stored in an audience measurement database, wherein the audience measurement database comprises, for each of a plurality of candidate device identifiers, a corresponding set of candidate device attributes;
based on the comparison, selecting, from a set of candidate device attributes, a set of target device attributes corresponding to a target device identifier;
determining a number of occurrences of the set of target device attributes in the network traffic data; and
based on a determination that the number of occurrences is above a threshold, outputting the target device identifier as the device identifier that corresponds to the user agent.
12 . The system of claim 11 , wherein determining the number of occurrences of the set of target device attributes comprises:
selecting a first target device attribute and a second target device attribute; and
determining a number of occurrences of a combination of the first target device attribute and the second target device attribute in the network traffic data.
13 . The system of claim 11 , wherein the client device is a mobile phone.
14 . The system of claim 11 , wherein the operations further comprise:
selecting one or more portions of the string of characters, each portion of the string of characters defining a respective client device attribute.
15 . The system of claim 14 , wherein the operations further comprise:
providing the one or more portions of the string of characters to a validation engine, wherein the validation engine is configured to, for each of the one or more portions of the string of characters:
process the portion of the string of characters to generate an output indicating that the portion of the string of characters represents a valid client device attribute or an invalid client device attribute.
16 . The system of claim 11 , wherein the network traffic data is collected by a streaming meter that is located at the media exposure measurement location and that is communicatively coupled to the client device, and wherein the streaming meter is configured to monitor the network to collect the network traffic data.
17 . The system of claim 11 , wherein the two or more client device attributes comprise two or more of: a type of the client device, a model of the client device, a make of the client device, or an operating system associated with the client device.
18 . The system of claim 11 , wherein the set of candidate device attributes in the audience measurement database are provided by users of devices associated with the media exposure measurement location.
19 . The system of claim 11 , further comprising:
determining a confidence score for the target device identifier; and
outputting the confidence score in addition to the target device identifier that corresponds to the user agent.
20 . A non-transitory computer-readable storage medium, having stored thereon program instructions that, upon execution by a processor, cause performance of a set of operations for mapping a user agent included in network traffic data onto a device identifier associated with a client device at a media exposure measurement location, the operations comprising:
obtaining the network traffic data comprising at least one user agent, wherein the user agent is associated with the client device coupled to a network at the media exposure measurement location, and wherein the user agent comprises a string of characters defining client device attributes;
comparing two or more of the client device attributes to candidate device attributes stored in an audience measurement database, wherein the audience measurement database comprises, for each of a plurality of candidate device identifiers, a corresponding set of candidate device attributes;
based on the comparison, selecting, from a set of candidate device attributes, a set of target device attributes corresponding to a target device identifier;
determining a number of occurrences of the set of target device attributes in the network traffic data; and
based on a determination that the number of occurrences is above a threshold, outputting the target device identifier as the device identifier that corresponds to the user agent.