Abstract: In one embodiment, a method includes identifying a particular item of interest of a user; determining a grouping of a number of items that are similar to the particular item; automatically creating a new video by combining the particular item and the respective number of grouped items that are similar to the particular item in accordance with a video-creation template; and providing the created video for display on a client device of the user.

Abstract: In one embodiment, a method includes identifying a particular item of interest of a user; determining a grouping of a number of items that are similar to the particular item; automatically creating a new video by combining the particular item and the respective number of grouped items that are similar to the particular item in accordance with a video-creation template; and providing the created video for display on a client device of the user.

Abstract: In one embodiment, a method includes accessing data of a number of items from a third-party computing system; identifying a subset of the number of items based on a value of a ranking model for each identified item being higher than a pre-determined threshold value; for each identified item of the subset, determining a number of similar items from the number of items; receiving a template for a video from the third-party computing system; for each of the identified items, generating a video incorporating the identified item and the respective number of similar items in accordance with the template; caching the generated videos; and providing for display on a client device of a user, a particular one of the videos selected based on information of the user.

Abstract: A system transmits selected news feed stories to a client device in advance of receiving a request for news feed stories. As a result, stories are immediately available for viewing when a user interacts with the system. The system selects news feed stories to push based on criteria such as a likelihood that a user will interact with a story and the sizes of pushed stories. For example, the system selects news feed stories such that a total size of stories selected does not exceed a threshold value based on local memory at the client device. The system may determine a scheduled time at which the stories are selected and pushed. The scheduled time is based on factors including patterns of network connection speed or past user interactions, for example, a time range of the day during which the user most frequently viewed pushed stories.

Abstract: A mobile device receives ranked news feed stories from a server of a social networking system. The mobile device determines whether to adjust the ranking based on local information generated by applications executing on the mobile device or hardware of the mobile device. Examples of local information of the mobile device include information describing the mobile devices' network connection, geographical location, sensor readings, downloaded data on memory storage, and interactions of software applications executing on the mobile device. For example, if a network co-processor of a mobile device detects a slow network connection, the mobile device lowers the ranking of news feed stories expected to require further use of network bandwidth.

Abstract: A system transmits selected news feed stories to a client device in advance of receiving a request for news feed stories. As a result, stories are immediately available for viewing when a user interacts with the system. The system selects news feed stories to push based on criteria such as a likelihood that a user will interact with a story and the sizes of pushed stories. For example, the system selects news feed stories such that a total size of stories selected does not exceed a threshold value based on local memory at the client device. The system may determine a scheduled time at which the stories are selected and pushed. The scheduled time is based on factors including patterns of network connection speed or past user interactions, for example, a time range of the day during which the user most frequently viewed pushed stories.

Abstract: Embodiments relate to providing a recorded gameplay session of an interactive content controlled by a broadcasting user. While the broadcasting user is controlling the interactive content being recorded, the inputs provided by the broadcasting user for interacting with the interactive content are recorded. Properties of objects in the interactive content being controlled by the broadcasting user are modified in view of the inputs provided by the broadcasting user. Furthermore, the properties of the objects in the interactive content being controlled by the broadcasting user are periodically recorded. The recorded inputs provided by the broadcasting user and the recorded properties of the objects in the interactive content are used to provide a viewing user a recording of the gameplay session of the interactive content controlled by the broadcasting user.

Abstract: Embodiments relate to providing a recorded gameplay session of an interactive content controlled by a broadcasting user. While the broadcasting user is controlling the interactive content being recorded, the inputs provided by the broadcasting user for interacting with the interactive content are recorded. Properties of objects in the interactive content being controlled by the broadcasting user are modified in view of the inputs provided by the broadcasting user. Furthermore, the properties of the objects in the interactive content being controlled by the broadcasting user are periodically recorded. The recorded inputs provided by the broadcasting user and the recorded properties of the objects in the interactive content are used to provide a viewing user a recording of the gameplay session of the interactive content controlled by the broadcasting user.

Abstract: A mobile device receives ranked news feed stories from a server of a social networking system. The mobile device determines whether to adjust the ranking based on local information generated by applications executing on the mobile device or hardware of the mobile device. Examples of local information of the mobile device include information describing the mobile devices' network connection, geographical location, sensor readings, downloaded data on memory storage, and interactions of software applications executing on the mobile device. For example, if a network co-processor of a mobile device detects a slow network connection, the mobile device lowers the ranking of news feed stories expected to require further use of network bandwidth.

Abstract: A system transmits selected news feed stories to a client device in advance of receiving a request for news feed stories. As a result, stories are immediately available for viewing when a user interacts with the system. The system selects news feed stories to push based on criteria such as a likelihood that a user will interact with a story and the sizes of pushed stories. For example, the system selects news feed stories such that a total size of stories selected does not exceed a threshold value based on local memory at the client device. The system may determine a scheduled time at which the stories are selected and pushed. The scheduled time is based on factors including patterns of network connection speed or past user interactions, for example, a time range of the day during which the user most frequently viewed pushed stories.

Abstract: Physical social actions are conveniently detected, characterized, and provided to a social networking system. This improves the user experience of the social networking system by more thoroughly recording the social actions of users occurring outside a social graph. This has the effect of extending an open social graph, which typically refers to social actions taken outside the social networking system but within a computer network, to physical social actions. By providing characterized physical social actions to the social networking system, the open social graph is extended to include physical social actions.

Abstract: Systems, methods, and non-transitory computer-readable media can determine a predicted bandwidth value for communications between a first computing system and a second computing system associated with a user of the first computing system. The first computing system can categorize the predicted bandwidth value into a connection quality class of a plurality of connection quality classes. The first computing system can customize provision of information from the first computing system to the second computing system based on the connection quality class.

Abstract: Physical social actions are conveniently detected, characterized, and provided to a social networking system. This improves the user experience of the social networking system by more thoroughly recording the social actions of users occurring outside a social graph. This has the effect of extending an open social graph, which typically refers to social actions taken outside the social networking system but within a computer network, to physical social actions. By providing characterized physical social actions to the social networking system, the open social graph is extended to include physical social actions.