Abstract: Systems, methods, and non-transitory computer-readable media can select a set of selected pages from a plurality of pages on a social networking system based on page selection criteria. A set of potential stories from the set of selected pages is aggregated. The set of potential stories are ranked based on ranking criteria. An administrator feed associated with a first page is generated, the administrator feed comprising a plurality of stories from the set of potential stories based on the ranking the set of potential stories.

Abstract: Systems, methods, and non-transitory computer readable media can determine one or more user-related metrics relating to each page of a plurality of pages associated with an administrator based on a first machine learning model. One or more recommendations relating to each page of the plurality of pages can be determined based on a second machine learning model. One or more pages of the plurality of pages for which to display cards including page updates in a feed of the administrator can be determined, based on the determined user-related metrics and the determined recommendations.

Abstract: Systems, methods, and non-transitory computer readable media can receive a request from a user to access information associated with an entity through an interface supported on a particular surface. A plurality of candidate content items of a content type associated with the entity can be ranked for the user and the particular surface based on a machine learning model. At least one of the ranked plurality of candidate content items of the content type can be provided for display through the interface.

Abstract: Systems, methods, and non-transitory computer readable media can receive a request from a client for one or more actions associated with a page for a particular channel for a particular user. A plurality of actions associated with the page can be obtained. The plurality of actions can be ranked for the particular channel for the particular user based at least in part on a machine learning model. One or more actions from the ranking the plurality of actions can be provided to the client for rendering in a user interface.

Abstract: Systems, methods, and non-transitory computer-readable media can select a set of selected pages from a plurality of pages on a social networking system based on page selection criteria. A set of potential stories from the set of selected pages is aggregated. The set of potential stories are ranked based on ranking criteria. An administrator feed associated with a first page is generated, the administrator feed comprising a plurality of stories from the set of potential stories based on the ranking the set of potential stories.

Abstract: Systems, methods, and non-transitory computer-readable media according to certain aspects can obtain a goal associated with a page provided by a social networking system. Potential recommendations for the page can be determined based on a first machine learning model. The potential recommendations can be ranked based on a second machine learning model to identify a subset of recommendations relating to the goal.

Abstract: Systems, methods, and non-transitory computer readable media can determine one or more user-related metrics relating to each page of a plurality of pages associated with an administrator based on a first machine learning model. One or more recommendations relating to each page of the plurality of pages can be determined based on a second machine learning model. One or more pages of the plurality of pages for which to display cards including page updates in a feed of the administrator can be determined, based on the determined user-related metrics and the determined recommendations.