Abstract: To predict a life change event for a user of the social networking system, such as a change in marital status, relationship status, employment status, etc., the disclosed system generates a training set of data comprising historical data of other users who have gone through a life change event. The system uses the training set data to generate a prediction algorithm using machine learning models. Furthermore, the system inputs the user data to the prediction algorithm to retrieve a prediction of whether the user will undergo one or more life change events. The system updates the user's profile to indicate the life change event and provides advertisements to the user responsive to the prediction of one or more life change events.

Abstract: A social networking system facilitates a user's creation of a group of other users from among the user's connections in the user's social network. The created groups may be used, for example, to publish information to certain user-defined groups or to define privacy settings or other access rights to the user's content according to such user-defined groups. When a user adds connections to a group, the social networking system determines suggested connections that have not been added to the group, based on a similarity of the suggested connections with one or more of the connections who have been added to the group. These suggested connections are then presented to the user to facilitate the creation of the group. Both positive and negative feedback may be used to generate a useful set of suggestions, which may be updated as the user further defines the group.