Abstract:
A social networking system receives contact information from a social networking system user. The received contact information is stored and associated with a user profile in the social networking system including information matching at least a portion of the stored content information. This increases the information associated with the user profile. Subsequently received content information is compared to user profiles and stored contact information associated with one or more user profiles. User profiles including information matching at least a portion of the subsequently received content information or associated with stored contact information matching at least a portion of the subsequently received content information are identified as potential connections for the user providing the subsequently received contact information.
Abstract:
When a request to connect a requesting user to a target user is received by the social networking system, information associated with the requesting user and with users connected to the target user is retrieved. A fraud probability score indicating a probability that the requesting user is impersonating a user connected to the target user is determined based on the information associated with the requesting user and with users connected to the target user. Based on the fraud probability score, a determination is made whether the requesting user is a suspected imposter and remedial action is taken if imposter is suspected.
Abstract:
A social networking system receives a selection of user characteristics defining a benchmark audience and a target audience, and generates audience metrics that compare the audiences across a set of user characteristics. These user characteristics include demographics, interests, purchasing activity, and actions on the social networking system. The audience metrics are provided to an advertiser who may select additional user characteristics to refine the benchmark or target audiences. The audience metrics may include an affinity score that compares the audience metrics for a particular type of interaction, and may normalize the frequency of interactions relative to interactions of the audience as a whole. Advertisers may use the defined audiences to establish targeting criteria for an advertisement, and may use existing targeting criteria to seed the selection of an audience.
Abstract:
When a request to connect a requesting user to a target user is received by the social networking system, information associated with the requesting user and with users connected to the target user is retrieved. A fraud probability score indicating a probability that the requesting user is impersonating a user connected to the target user is determined based on the information associated with the requesting user and with users connected to the target user. Based on the fraud probability score, a determination is made whether the requesting user is a suspected imposter and remedial action is taken if imposter is suspected.
Abstract:
A social networking system receives contact information from a social networking system user. The received contact information is stored and associated with a user profile in the social networking system including information matching at least a portion of the stored content information. This increases the information associated with the user profile. Subsequently received content information is compared to user profiles and stored contact information associated with one or more user profiles. User profiles including information matching at least a portion of the subsequently received content information or associated with stored contact information matching at least a portion of the subsequently received content information are identified as potential connections for the user providing the subsequently received contact information.
Abstract:
A social networking system receives contact information from a social networking system user. The received contact information is stored and associated with a user profile in the social networking system including information matching at least a portion of the stored content information. This increases the information associated with the user profile. Subsequently received content information is compared to user profiles and stored contact information associated with one or more user profiles. User profiles including information matching at least a portion of the subsequently received content information or associated with stored contact information matching at least a portion of the subsequently received content information are identified as potential connections for the user providing the subsequently received contact information.
Abstract:
A social networking system receives contact information from a social networking system user. The received contact information is stored and associated with a user profile in the social networking system including information matching at least a portion of the stored content information. This increases the information associated with the user profile. Subsequently received content information is compared to user profiles and stored contact information associated with one or more user profiles. User profiles including information matching at least a portion of the subsequently received content information or associated with stored contact information matching at least a portion of the subsequently received content information are identified as potential connections for the user providing the subsequently received contact information.
Abstract:
A social networking system receives a selection of user characteristics defining a benchmark audience and a target audience, and generates audience metrics that compare the audiences across a set of user characteristics. These user characteristics include demographics, interests, purchasing activity, and actions on the social networking system. The audience metrics are provided to an advertiser who may select additional user characteristics to refine the benchmark or target audiences. The audience metrics may include an affinity score that compares the audience metrics for a particular type of interaction, and may normalize the frequency of interactions relative to interactions of the audience as a whole. Advertisers may use the defined audiences to establish targeting criteria for an advertisement, and may use existing targeting criteria to seed the selection of an audience.