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 increase engagement with a social networking system. In one embodiment, an engagement level of a user with a social networking system is monitored. A low engagement user type associated with the user is identified from a plurality of low engagement user types. It is determined whether the engagement level of the user is less than a threshold. If so, a communication is provided for the user based on the low engagement user type associated with the user. The communication may be a notification or a digest communication.
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 increase engagement with a social networking system. In one embodiment, an engagement level of a user with a social networking system is monitored. A low engagement user type associated with the user is identified from a plurality of low engagement user types. It is determined whether the engagement level of the user is less than a threshold. If so, a communication is provided for the user based on the low engagement user type associated with the user. The communication may be a notification or a digest communication.
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:
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.