Abstract: An online system selects advertisements for inclusion in a scrollable advertisement unit that includes a display area and multiple advertisements, each associated with a position in the scrollable advertisement unit. Positions in the scrollable advertisement unit are ranked based on a measure of predicted performance of an advertisement in each position. Advertisements are ranked based on a probability of being viewed by a user if associated with a particular position in the scrollable advertisement unit and, optionally, on a probability of presenting an advertisement based on characteristics of the advertisement. The position ranking and the advertisement ranking are used to associate advertisements with positions. For example, an advertisement is associated with a position having a location in the position ranking corresponding to the advertisement's position in the advertisement ranking.

Abstract: An online system transmits a notification including a reference to an application to a client device associated with a user. Upon receiving an interaction with the reference to the application, the online system may transmit instructions for retrieving the application to an additional client device associated with the user. For example, if the client device used to interact with the reference has a device type different than a device type associated with the application, the online system selects an additional client device having a device type matching the device type associated with the application to receive the instruction for retrieving the application.

Abstract: A social networking system may infer interests based on extracted topics from content items on the social networking system. A user's comments and page likes in a social networking system are used to infer topics in which the user is interested. Topics may also be automatically extracted from users' posts, and the extracted topics may be generalized using a category tree to identify additional topics for the user. The social networking system may target content such as advertisements to users based on these extracted topics. For example, the social networking system may boost stories related to the extracted topics in the user's content feeds, append stories about the extracted topics to advertisements that are also related to the topics, append advertisements to stories about the extracted topics, or use the extracted topics as targeting criteria for an advertisement.