Abstract:
A social networking system prices advertisements presented to a user of a social networking system via a client device in a state that provides the user with limited functionality by applying discount factors to bid amounts associated with advertisements selected for presentation. A discount factor is based on the likelihood of the user viewing or interacting with an advertisement via the social networking system presented while the client device is in the state providing the user with limited functionality. This likelihood is determined based on information including a history of user interaction with the client device and contextual information indicating whether the client device is in use.
Abstract:
A social networking system prices advertisements presented to a user of a social networking system via a client device in a state that provides the user with limited functionality by applying discount factors to bid amounts associated with advertisements selected for presentation. A discount factor is based on the likelihood of the user viewing or interacting with an advertisement via the social networking system presented while the client device is in the state providing the user with limited functionality. This likelihood is determined based on information including a history of user interaction with the client device and contextual information indicating whether the client device is in use.
Abstract:
A social networking system selects advertisements for presentation to a user while a client device used by the user is in a state that provides limited functionality to the user, such as a locked state. Based on objectives associated with various advertisements, the social networking system determines interactions associated with advertisements and selects advertisements associated with interactions capable of being performed while the client device is in the state that provides limited functionality to the user or associated with no interaction. The social networking system sends the advertisements to the client device for display to the user while the client device is in the state of limited functionality.
Abstract:
Systems, methods, and non-transitory computer-readable media can determine that a candidate is likely to leave a current employer employing the candidate based on one or more outreach timing machine learning models. An outreach message for the candidate is generated based on one or more content generation machine learning models in response to the determining that the candidate is likely to leave the current employer. The outreach message is transmitted to the candidate.