Facebook, Inc.

Sue Ann Hong

Gunjit Singh

Kyle Edward Johnson

Atif Zahoor Khan

Gang Wu

Rituraj Kirti

Haibin Cheng

Xingyao Ye

Boris Pierre Arnoux

Vladislav Isenbaev

An online system identifies seed users of high value to a sponsored content provider. Characteristics of the seed users are identified, and additional users having a threshold measure of similarity to the seed users are identified based on the characteristics. A score is determined for each of the additional users based on the measure of similarity. The seed users are placed in an initial tier of a tiered set of users for the sponsored content, and the additional users are placed in additional tiers of the tiered set of users based upon the determined scores such that each additional tier includes those users of the additional users having a specified range of determined scores, the tiers of the tiered set of users ranked according to the determined scores of users within each tier.

Grouping users into tiers based on similarity to a group of seed users

A social networking system presents users with a content items and ad requests, which may include targeting criteria specifying a topic. Interactions by users who were presented with an advertisement from an ad request including targeting criteria specifying the topic are stored by the social networking system and used to identify a cluster group of additional users having characteristics similar to characteristics of users who were presented with the advertisement from the ad request including targeting criteria specifying the topic and who interacted with the advertisement. The social networking system determines scores for additional users in the cluster group based on measures of similarity between the additional users and the users who were presented with the advertisement and who interacted with the advertisement. Based on the determined scores, the social networking system associates additional users in the cluster group with the topic.

Clustering users of a social networking system based on user interactions with content items associated with a topic

A social networking system selects advertisements for a user based on user characteristics of the user in response to a request to present an advertisement to the user. To increase the number of advertisements eligible for presentation to the user, the social networking system associates the user with one or more cluster groups associated with targeting criteria that are not satisfied by the user's characteristics. To determine whether to associate a user with a cluster group, the social networking system determines a cluster score for the cluster group based on the user's characteristics. If the cluster score equals or exceeds a cluster cutoff score for the cluster group, the user is associated with the cluster group. The cluster cutoff score may be determined based on an estimated distribution of users so that a target number or percentage of users have cluster scores less than the cluster cutoff score.

Runtime expansion of targeting criteria based on user characteristics

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San Francisco, CA, United States of America

Sue Ann Hong