Abstract: Methods, systems, and storage media for generating polls in an end-to-end encrypted messaging platform are disclosed. Exemplary implementations may: initiate, by an initiator, a poll comprising a poll name, an ending time, and response choices; generate a message to a group of users regarding the poll; for each user of the group of users, generate a key pair comprising a chain key and a signature key; receive, from a user of the group of users, a selection comprising at least one of the response choices; and cause display of the selection through the poll.

Abstract: Methods, systems, and storage media for routing messages through a secure messaging platform are disclosed. Exemplary implementations may: receive, at a smart router, a request to send a message to at least one recipient; route, via the smart router, the request to a marketplace of delivery aggregators; select at least one of the delivery aggregators for handling the request; and deliver, via the selected at least one delivery aggregator, the message to the at least one recipient.

Abstract: An online system is configured to recommend a live video to a target user by presenting the live video in the target user's newsfeed or other location. The online system receives a plurality of live videos for streaming to its users. To recommend a live video, the online system dynamically identifies a topic of each of the plurality of live videos during the streaming. The online system further selects a group of candidate live videos, each of which has an identified topic matching an interest of the target user. The online system ranks the candidates based on a probability that the target user would positively interact with each candidate live video if the candidate live video is presented to the target user. Then the online system provides a candidate above a threshold level in the ranking for display to the target user, e.g., in a newsfeed of the target user.

Abstract: An online system is configured to recommend a live video to a target user by presenting the live video in the target user's newsfeed or other location. The online system receives a plurality of live videos for streaming to its users. To recommend a live video, the online system dynamically identifies a topic of each of the plurality of live videos during the streaming. The online system further selects a group of candidate live videos, each of which has an identified topic matching an interest of the target user. The online system ranks the candidates based on a probability that the target user would positively interact with each candidate live video if the candidate live video is presented to the target user. Then the online system provides a candidate above a threshold level in the ranking for display to the target user, e.g., in a newsfeed of the target user.

Abstract: An online system provides video recommendations to a target user of the online system as a supplement to videos provided to the target user that were posted by the user's connections in the online system. The recommended videos are selected from publicly available video content and are likely to be of interest to the target user. The online system has video candidate generators that select video candidates based on a variety of selection criteria. The selected video candidates are filtered to identify inappropriate content or videos that the target user has already viewed for elimination from candidacy. The filtered video candidates are ranked based on weights of features of the video candidates. Based on the ranking, the online system selects videos above a threshold as recommendations to the target user.

Abstract: Systems, methods, and non-transitory computer-readable media can detect a trigger to generate a set of media content items associated with at least one of a particular media content item or a user viewing the particular media content item. A plurality of content generators can be utilized to generate a plurality of subsets of media content items. Each of the plurality of content generators can identify a respective subset out of the plurality of subsets of media content items based on at least one of information associated with the particular media content item or information associated with the user viewing the particular media content item. At least some media content items in at least some of the plurality of subsets of media content items can be ranked based on respective information associated with each media content item.

Abstract: An online system is configured to recommend a live video to a target user by presenting the live video in the target user's newsfeed or other location. The online system receives a plurality of live videos for streaming to its users. To recommend a live video, the online system dynamically identifies a topic of each of the plurality of live videos during the streaming. The online system further selects a group of candidate live videos, each of which has an identified topic matching an interest of the target user. The online system ranks the candidates based on a probability that the target user would positively interact with each candidate live video if the candidate live video is presented to the target user. Then the online system provides a candidate above a threshold level in the ranking for display to the target user, e.g., in a newsfeed of the target user.

Abstract: Systems, methods, and non-transitory computer-readable media can detect a trigger to generate a set of media content items associated with at least one of a particular media content item or a user viewing the particular media content item. A plurality of content generators can be utilized to generate a plurality of subsets of media content items. Each of the plurality of content generators can identify a respective subset out of the plurality of subsets of media content items based on at least one of information associated with the particular media content item or information associated with the user viewing the particular media content item. At least some media content items in at least some of the plurality of subsets of media content items can be ranked based on respective information associated with each media content item.

Abstract: Systems, methods, and non-transitory computer-readable media can determine at least a first category of content items and a second category of content items to be included in a content feed for a user. A ranking for content items included in the first category is determined and a ranking for content items included in the second category is also determined. An interface that presents the content feed including one or more ranked content items from the first category and one or more ranked content items from the second category is provided.

Abstract: An online system provides video recommendations to a target user of the online system as a supplement to videos provided to the target user that were posted by the user's connections in the online system. The recommended videos are selected from publicly available video content and are likely to be of interest to the target user. The online system has video candidate generators that select video candidates based on a variety of selection criteria. The selected video candidates are filtered to identify inappropriate content or videos that the target user has already viewed for elimination from candidacy. The filtered video candidates are ranked based on weights of features of the video candidates. Based on the ranking, the online system selects videos above a threshold as recommendations to the target user.

Abstract: Systems, methods, and non-transitory computer-readable media can detect a trigger to generate a set of media content items associated with at least one of a particular media content item or a user viewing the particular media content item. A plurality of content generators can be utilized to generate a plurality of subsets of media content items. Each of the plurality of content generators can identify a respective subset out of the plurality of subsets of media content items based on at least one of information associated with the particular media content item or information associated with the user viewing the particular media content item. At least some media content items in at least some of the plurality of subsets of media content items can be ranked based on respective information associated with each media content item.