Socioeconomic group classification based on user features

    公开(公告)号:US10607154B2

    公开(公告)日:2020-03-31

    申请号:US15221587

    申请日:2016-07-27

    Applicant: Facebook, Inc.

    Abstract: An online system uses classifiers to predict the socioeconomic group of users of the online system. The classifiers use models that are trained using features based on global information about a population of users such as demographic information, device ownership, internet usage, household data, and socioeconomic status. The global information can be aggregated from market research questionnaires and provided to the online system. The classifiers input information about a user and output a probability that the user belongs to a given socioeconomic group. The input information is based on a user profile on the online system associated with the user as well as actions performed by the user on the online system. Thus, the online system can predict the user's socioeconomic group without using the user's income information. The online system can generate content for presentation to the user based on the predicted socioeconomic group.

    SOCIOECONOMIC GROUP CLASSIFICATION BASED ON USER FEATURES

    公开(公告)号:US20180032883A1

    公开(公告)日:2018-02-01

    申请号:US15221587

    申请日:2016-07-27

    Applicant: Facebook, Inc.

    CPC classification number: G06N20/00 G06Q30/0201 G06Q30/0202 G06Q30/0269

    Abstract: An online system uses classifiers to predict the socioeconomic group of users of the online system. The classifiers use models that are trained using features based on global information about a population of users such as demographic information, device ownership, internet usage, household data, and socioeconomic status. The global information can be aggregated from market research questionnaires and provided to the online system. The classifiers input information about a user and output a probability that the user belongs to a given socioeconomic group. The input information is based on a user profile on the online system associated with the user as well as actions performed by the user on the online system. Thus, the online system can predict the user's socioeconomic group without using the user's income information. The online system can generate content for presentation to the user based on the predicted socioeconomic group.

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