Facebook, Inc.

Taylor Gordon

Rui Wang

Lars Seren Backstrom

Fei Huang

Thomas Frederick Dimson

Justin Moore

Jan Kalis

Enoch Chee-Lok Lau

Systems, methods, and non-transitory computer readable media can perform a first ranking to rank each ephemeral content item collection of a plurality of ephemeral content item collections based on a probability of a user selecting the ephemeral content item collection. One or more ephemeral content item collections from the first ranking to provide in an ephemeral content feed of the user can be selected. A second ranking to rank each ephemeral content item collection of the plurality of ephemeral content item collections other than the selected ephemeral content item collections from the first ranking based on a probability of the user spending time on the ephemeral content item collection can be performed. One or more ephemeral content item collections from the second ranking to provide in the ephemeral content feed of the user can be selected.

Systems and methods for ranking ephemeral content item collections associated with a social networking system

Systems, methods, and non-transitory computer-readable media can determine a first set of content items to be sent to a computing device of a user. A token is generated based at least in part on the first set of content items, the token being encoded with information for tracking content items sent to the computing device of the user. Data corresponding to the set of content items and the token is sent to the computing device of the user.

Systems and methods for providing content

Systems, methods, and non-transitory computer-readable media can generate a set of candidate content items from a plurality of content items that are available in the social networking system for a first user. A corresponding score for each of the candidate content items can be generated based at least in part on one or more social affinity coefficients corresponding to the first user and a respective second user associated with a candidate content item, wherein a social affinity coefficient provides a quantitative measurement of the strength of a relationship between two users. A first set of content items from the set of candidate content items can be determined based at least in part on the respective scores, wherein content items in the first set are included in a content feed provided to the first user.

Systems, methods, and non-transitory computer readable media can perform a first ranking to rank each ephemeral content item collection of a plurality of ephemeral content item collections based on a probability of a user selecting the ephemeral content item collection, each ephemeral content item collection of the plurality of ephemeral content item collections including one or more ephemeral content items. One or more ephemeral content item collections from the first ranking can be provided in an ephemeral content feed of the user. A selection by the user of an ephemeral content item collection provided in the ephemeral content feed can be received. A second ranking to rank each ephemeral content item collection of the ephemeral content item collections provided in the ephemeral content feed other than the selected ephemeral content item collection based on a probability of the user spending time on the ephemeral content item collection can be performed.

Systems, methods, and non-transitory computer readable media can determine a value of a boosting parameter, wherein the boosting parameter is indicative of a value of feedback to a first account type. Respective scores of a plurality of content items that are candidates for a feed of a user can be determined, wherein the plurality of content items are associated with at least one of the first account type or a second account type. Respective scores of content items associated with the first account type in the plurality of content items can be adjusted based on the value of the boosting parameter. The plurality of content items can be ranked based on the respective scores of the plurality of content items.

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New York, NY, United States of America

Taylor Gordon