Abstract: In one embodiment, a method includes receiving a number of notifications of activity relevant to a user. Each notification has an associated type. The method also includes calculating an estimated click-through rate (CTR) for each notification based at least in part on the type associated with each notification; determining a push threshold value for each notification based at least in part on the estimated CTR for each notification; and sending one or more of the notifications to the user. Each of the sent notifications has a push threshold value higher than a pre-determined push threshold value.

Abstract: In one embodiment, a method includes receiving a number of notifications of one or more activities relevant to a user. Each notification has an associated receipt time and type of notification. The method also includes aggregating one or more of the notifications based on the type of notification; determining a sending time to send the aggregated notifications based at least in part on determining that a pre-determined amount of time that has elapsed from a receipt time of a most recent one of the aggregated notifications; and sending the aggregated notifications to the user based on the sending time.

Abstract: In one embodiment, a method includes receiving a number of notifications of activity relevant to a user. Each notification has an associated type. The method also includes calculating an inferred subscription level based at least in part on the type associated with each notification; classifying the notifications based on the inferred subscription of each notification; and sending one or more of the notifications to the user. Each of the sent notifications has an inferred subscription level higher than a pre-determined threshold subscription level.

Abstract: Techniques to optimize messages sent to a user of a social networking system. In one embodiment, information about the user may be collected by the social networking system. The information may be applied to train a model for determining likelihood of a desired action by the user in response to candidate messages that may be provided for the user. The social networking system may provide to the user a message from the candidate messages with a selected likelihood of causing the desired action.

Abstract: In one embodiment, a method includes accessing for a user one or more electronic notifications that include information about a social network. The social network includes a plurality of nodes connected by a plurality of edges, with at least one node corresponding to the user. The method further includes determining, for each of the electronic notifications, a score that estimates whether a user interaction with the social network will result if the electronic notification is provided to the user. The method further includes determining, based at least in part on the determined scores, an action to take with respect to the electronic notifications.

Abstract: In one embodiment, a method includes accessing for a user one or more electronic notifications that include information about a social network. The social network includes a plurality of nodes connected by a plurality of edges, with at least one node corresponding to the user. The method further includes determining, for each of the electronic notifications, a score that estimates whether a user interaction with the social network will result if the electronic notification is provided to the user. The method further includes determining, based at least in part on the determined scores, an action to take with respect to the electronic notifications.

Abstract: Techniques to optimize messages sent to a user of a social networking system. In one embodiment, information about the user may be collected by the social networking system. The information may be applied to train a model for determining likelihood of a desired action by the user in response to candidate messages that may be provided for the user. The social networking system may provide to the user a message from the candidate messages with a selected likelihood of causing the desired action.

Abstract: In one embodiment, a method includes one or more computing devices accessing a notification to be sent to a user, where the notification has a context. The method also includes one or more computing devices sending a request to a history service for historical notification data associated with the user with respect to the context of the notification and a ranking of the notification where the ranking indicates a probability of the user interacting with the notification. The method also includes one or more computing devices receiving the historical notification data and the ranking from the history service. Moreover, the method also includes one or more computing devices determining a notification policy to apply to the notification based at least in part on the context of the notification, the historical notification data, and the ranking. Furthermore, the method also includes one or more computing devices applying the notification policy to the notification to be sent to the user.

Abstract: Techniques to optimize messages sent to a user of a social networking system. In one embodiment, information about the user may be collected by the social networking system. The information may be applied to train a model for determining likelihood of a desired action by the user in response to candidate messages that may be provided for the user. The social networking system may provide to the user a message from the candidate messages with a selected likelihood of causing the desired action.

Abstract: In one embodiment, a method includes accessing for a user one or more electronic notifications that include information about a social network. The social network includes a plurality of nodes connected by a plurality of edges, with at least one node corresponding to the user. The method further includes determining, for each of the electronic notifications, a score that estimates whether a user interaction with the social network will result if the electronic notification is provided to the user. The method further includes determining, based at least in part on the determined scores, an action to take with respect to the electronic notifications.

Abstract: In one embodiment, a method includes receiving a message associated with a user at an information exchange system. At least one correspondent associated with the user may be determined, based on the message. A social connection between the user and the at least one correspondent may be assessed with respect to a social-networking system. The information exchange system may provide an interface for display to the user, the interface comprising information associated with the message. If the social connection is confirmed, the interface may include social-networking information associated with the at least one correspondent. Otherwise, the interface may provide functionality to create a social connection between the user and the at least one correspondent with respect to the social-networking system.

Abstract: In one embodiment, a method includes receiving a message associated with a user at an information exchange system. At least one correspondent associated with the user may be determined, based on the message. A social connection between the user and the at least one correspondent may be assessed with respect to a social-networking system. The information exchange system may provide an interface for display to the user, the interface comprising information associated with the message. If the social connection is confirmed, the interface may include social-networking information associated with the at least one correspondent. Otherwise, the interface may provide functionality to create a social connection between the user and the at least one correspondent with respect to the social-networking system.

Abstract: Techniques to optimize messages sent to a user of a social networking system. In one embodiment, information about the user may be collected by the social networking system. The information may be applied to train a model for determining likelihood of a desired action by the user in response to candidate messages that may be provided for the user. The social networking system may provide to the user a message from the candidate messages with a selected likelihood of causing the desired action.

Abstract: Techniques to optimize messages sent to a user of a social networking system. In one embodiment, information about the user may be collected by the social networking system. The information may be applied to train a model for determining likelihood of a desired action by the user in response to candidate messages that may be provided for the user. The social networking system may provide to the user a message from the candidate messages with a selected likelihood of causing the desired action.

Abstract: To suggest new connections to a user of a social networking system, the system generates a set of candidate users to whom the user has not already formed a connection. The system determines the likelihood that the user will connect to each candidate user if suggested to do so, and it also computes the value to the social networking system if the user does connect to the candidate user. Then, the system computes an expected value score for each candidate user based on the corresponding likelihood and the value. The candidate users are ranked and the suggestions are provided to the user based on the candidate users' expected value scores. The social networking system can suggest other actions to a user in addition to forming a new connection with other users.

Abstract: In one embodiment, a method includes receiving a message associated with a user at an information exchange system. At least one correspondent associated with the user may be determined, based on the message. A social connection between the user and the at least one correspondent may be assessed with respect to a social-networking system. The information exchange system may provide an interface for display to the user, the interface comprising information associated with the message. If the social connection is confirmed, the interface may include social-networking information associated with the at least one correspondent. Otherwise, the interface may provide functionality to create a social connection between the user and the at least one correspondent with respect to the social-networking system.

Abstract: Techniques to optimize messages sent to a user of a social networking system. In one embodiment, information about the user may be collected by the social networking system. The information may be applied to train a model for determining likelihood of a desired action by the user in response to candidate messages that may be provided for the user. The social networking system may provide to the user a message from the candidate messages with a selected likelihood of causing the desired action.

Abstract: To suggest new connections to a user of a social networking system, the system generates a set of candidate users to whom the user has not already formed a connection. The system determines the likelihood that the user will connect to each candidate user if suggested to do so, and it also computes the value to the social networking system if the user does connect to the candidate user. Then, the system computes an expected value score for each candidate user based on the corresponding likelihood and the value. The candidate users are ranked and the suggestions are provided to the user based on the candidate users' expected value scores. The social networking system can suggest other actions to a user in addition to forming a new connection with other users.

Abstract: To suggest new connections to a user of a social networking system, the system generates a set of candidate users to whom the user has not already formed a connection. The system determines the likelihood that the user will connect to each candidate user if suggested to do so, and it also computes the value to the social networking system if the user does connect to the candidate user. Then, the system computes an expected value score for each candidate user based on the corresponding likelihood and the value. The candidate users are ranked and the suggestions are provided to the user based on the candidate users' expected value scores. The social networking system can suggest other actions to a user in addition to forming a new connection with other users.

Abstract: A social networking system may recommend a set of users to a viewing user for establishing new connections on the social networking system. Through a user interface, the viewing user may select filters based on characteristics and dimensions of user profile information. The recommended set of users may be ranked according to the selected filters by the number of mutual connections. Pre-populated filters may be selected and suggested based on information about the viewing user. Multiple filters may be selected by the viewing user, and filters may be based on any identifiable object in the social networking system, in one embodiment. The candidate recommended users may also be ranked based on predictions that the viewing user will initiate a request to connect with the candidate recommended users.