Facebook, Inc.

Deepa Diwakar

Lydia Han

Christopher Jon Lang

Daniil Burdakov

Aigerim Shorman

Harshdeep Singh

Tanner Cotant Christensen

Pradeep George Mathias

Tamar Bar Lev

Noah Bradley Blecher

Crystal Rhan-Tsor Chen

Karthik Narayan

Shupin Mao

Varun Kacholia

Sahil Prakash Thaker

Brett Welch

Yuanxuan Wang

Fidji Nahema Simo

An online system generates a feed of content items for a user subject to a limitation restricting the number of content items including video data ('video content items') included in the feed. If the user interacts with a video content item the feed, the online system selects candidate video content items based on characteristics of the video content item in the feed and characteristics of the user. The online system determines likelihoods of the user interacting with various candidate video content items and selects candidate video content items based on the determined likelihoods. To present the user with additional video content items, the online system generates an interface including the selected candidate video content items and presents the interface to the user. The interface may be presented in place of the feed or may be presented as within the feed and presents different video content items based on user interactions.

Presenting video content to online system users in response to user interactions with video content presented in a feed of content items

An online system customizes video conversations between users of the online system by providing graphics that are likely to interest the users. The online system may present composite views overlaying selected graphics on a video stream, which may be part of an augmented reality (AR) environment. The graphics include, for example, background graphics, masks, props, visual or particular effects, frames or borders, etc. The online system may use a machine learning model to predict whether a user is likely to select or interact with a particular graphic. The online system can also filter or rank graphics according to user affinities or user connections on the online system. Users may be encouraged to interact with the graphics that are customized to their specific interests, which can promote an engaging video conversation or AR experience.

Video stream customization using graphics

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Mountain View, CA, United States of America

Deepa Diwakar