Facebook, Inc.

Jonathan Daniel Sorg

Bradley Ray Green

Ken Taro Deeter

Robyn David Morris

Thomas Stocky

Jun Li

Gregory Joseph Klein

Jason Eric Brewer

Antoine Joseph Atallah

Komal Kapoor

Jerry Ju

Andrew Rocco Tresolini Fiore

David Tomotsu Sasaki

Systems, methods, and non-transitory computer-readable media can determine a plurality of candidate entities for recommendation to a user of a social networking system. A predicted activity objective value model configured to calculate activity stores for candidate entities is established. The activity score is indicative of the probability of future activity on the social networking system by a candidate entity. A first activity score is determined for each of the plurality of candidate entities based on the predicted activity object value model and a first set of feature values. A second activity score is determined for each of the plurality of candidate entities based on the predicted activity object value model and a second set of feature values that is different from the first set of feature values. A first entity is selected of the plurality of candidate entities based on the first and second activity scores.

Systems and methods for predicting page activity to optimize page recommendations

A social networking system analyzes a user's interactions with objects linked to bookmarks associated with the user to generate a score for each bookmark. The score represents or is based on the probability that the user will access the bookmark or the linked object. For example, the score is a predicted click-through rate for the bookmark. Based on the scores, a subset of the bookmarks is selected for presentation to the user. Additionally, the scores may be used to order the selected subset of the bookmarks. Hence, the bookmarks that the user is most likely to access are presented while the bookmarks the user is less likely to access may be hidden.

Ordering of bookmarks for objects in a social networking system

In one embodiment, a set of user groups of a social-networking system may be accessed. A first subset of the user groups may be determined for a particular user of the social-networking system, based on one or more filtering criteria. A number of recommendation-source processes may be applied to the first subset to determine a number of second subsets of the first set. Each recommendation-source process may represent a particular recommendation source. The second subsets may be combined into a list of user groups. The list of user groups may be ranked, and sent to the particular user.

Ranking and filtering groups recommendations

A system identifies unconnected content items of high quality and provides the unconnected content items for display to a user. The method comprises receiving several content items posted on pages of a social networking system. The system then determines a subset of those content items (e.g., high quality content items). A topic is then extracted from each of the subset of content items. The topic is mapped to one or more related pages of the social networking system that represent an expanded set of pages associated with the content item. For each of the related pages, a user is identified who is connected to the related page. Finally, the content item (e.g., a high quality content item) is provided to the user for display in the user's newsfeed.

Determining stories of interest based on quality of unconnected content

A social networking system provides a content feed to a client device associated with the user of a social networking system, the content feed including a plurality of content items. The social networking system identifies a read section and an unread section of the content feed. The social networking system receives a request for a subsequent content feed from a client device associated with the user. The social networking system identifies new content items that are associated with users of the social networking system. The social networking system generates a current content segment that includes the new content items and the unread section of the content feed, and generates the subsequent content feed by inserting the current content segment before or after the read section of the content feed. The social networking system provides a portion of the subsequent content feed to the client device.

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Seattle, WA, United States of America

Jonathan Daniel Sorg