Abstract: In one embodiment, a method includes one or more computing devices ranking multiple users of a social-networking system based on one or more criteria associated with a spotlight content item, wherein the spotlight content item is associated with a node in a social graph associated with the social-networking system, and wherein at least one of the criteria is based on social-networking information for each of the user, verifying the ranked users, wherein the verifying comprises confirming or eliminating each of the ranked users based on recent interactions by the ranked users with social-networking information corresponding to the node associated with the spotlight content item, and sending a notification about the spotlight content item to each of the confirmed users in accordance with a batching protocol, wherein the batching protocol is determined based at least in part on rankings for each of the confirmed users.

Abstract: Exemplary embodiments relate to techniques for applying media effects to a video stream. For example, media effects may be applied and/or altered based on input from viewers or participants in the video stream. Changes to the media effects may accumulate based on the inputs. In another example, viewership numbers or engagement with a user applying a media effect may alter the media effect. In a broadcast context, actions of the broadcast audience (e.g., as measured by polling) may affect the broadcast and hence the broadcaster. Object recognition and/or people recognition may be applied to cumulatively alter the media effects in an augmented reality context.

Abstract: In one embodiment, a method includes one or more computing devices ranking multiple users of a social-networking system based on one or more criteria associated with a spotlight content item, wherein the spotlight content item is associated with a node in a social graph associated with the social-networking system, and wherein at least one of the criteria is based on social-networking information for each of the user, verifying the ranked users, wherein the verifying comprises confirming or eliminating each of the ranked users based on recent interactions by the ranked users with social-networking information corresponding to the node associated with the spotlight content item, and sending a notification about the spotlight content item to each of the confirmed users in accordance with a batching protocol, wherein the batching protocol is determined based at least in part on rankings for each of the confirmed users.

Abstract: In one embodiment, a method includes one or more computing devices ranking multiple users of a social-networking system based on one or more criteria associated with a spotlight content item, wherein the spotlight content item is associated with a node in a social graph associated with the social-networking system, and wherein at least one of the criteria is based on social-networking information for each of the user, verifying the ranked users, wherein the verifying comprises confirming or eliminating each of the ranked users based on recent interactions by the ranked users with social-networking information corresponding to the node associated with the spotlight content item, and sending a notification about the spotlight content item to each of the confirmed users in accordance with a batching protocol, wherein the batching protocol is determined based at least in part on rankings for each of the confirmed users.

Abstract: Exemplary embodiments relate to techniques for applying media effects to a video stream. For example, media effects may be applied and/or altered based on input from viewers or participants in the video stream. Changes to the media effects may accumulate based on the inputs. In another example, viewership numbers or engagement with a user applying a media effect may alter the media effect. In a broadcast context, actions of the broadcast audience (e.g., as measured by polling) may affect the broadcast and hence the broadcaster. Object recognition and/or people recognition may be applied to cumulatively alter the media effects in an augmented reality context.

Abstract: Exemplary embodiments relate to techniques for applying media effects to a video stream. For example, media effects may be applied and/or altered based on input from viewers or participants in the video stream. Changes to the media effects may accumulate based on the inputs. In another example, viewership numbers or engagement with a user applying a media effect may alter the media effect. In a broadcast context, actions of the broadcast audience (e.g., as measured by polling) may affect the broadcast and hence the broadcaster. Object recognition and/or people recognition may be applied to cumulatively alter the media effects in an augmented reality context.

Abstract: Exemplary embodiments relate to techniques for applying media effects to a video stream. For example, media effects may be applied and/or altered based on input from viewers or participants in the video stream. Changes to the media effects may accumulate based on the inputs. In another example, viewership numbers or engagement with a user applying a media effect may alter the media effect. In a broadcast context, actions of the broadcast audience (e.g., as measured by polling) may affect the broadcast and hence the broadcaster. Object recognition and/or people recognition may be applied to cumulatively alter the media effects in an augmented reality context.

Abstract: In one embodiment, a method includes one or more computing devices ranking multiple users of a social-networking system based on one or more criteria associated with a spotlight content item, wherein the spotlight content item is associated with a node in a social graph associated with the social-networking system, and wherein at least one of the criteria is based on social-networking information for each of the user, verifying the ranked users, wherein the verifying comprises confirming or eliminating each of the ranked users based on recent interactions by the ranked users with social-networking information corresponding to the node associated with the spotlight content item, and sending a notification about the spotlight content item to each of the confirmed users in accordance with a batching protocol, wherein the batching protocol is determined based at least in part on rankings for each of the confirmed users.