Abstract:
An online system provides content items including URLs of third party websites to client devices. The client devices prefetch data from the third party website via the URL. The online system controls the prefetch rate for the client devices based on information received from the client devices. The online system may reduce the prefetch rate if an aggregate number of prefetches from the third party website during a time interval exceeds a prefetch quota. The online system may reduce the prefetch rate if the client devices indicate poor performance of the third party. The online system may determine whether to prefetch data from a URL included in a content item based on a likelihood of the user ignoring the content item if here is a delay in loading of the content item in the client device.
Abstract:
A user device requests a web page from a web server of a third-party website, which is separate from a social networking system. The web server from the third-party website sends a markup language document for the requested web page to the user device which includes an instruction for a browser application running on the user device to incorporate information obtained from the social networking system within the web page. Based on the instruction in the received markup language document, the user device requests personalized content from the social networking system, which generates the requested personalized content based on social information about the user. The user device then renders the web page with the personalized content contained in a frame and displays the rendered web page and the frame to the user.
Abstract:
A user device requests a web page from a web server of a third-party website, which is separate from a social networking system. The web server from the third-party website sends a markup language document for the requested web page to the user device which includes an instruction for a browser application running on the user device to incorporate information obtained from the social networking system within the web page. Based on the instruction in the received markup language document, the user device requests personalized content from the social networking system, which generates the requested personalized content based on social information about the user. The user device then renders the web page with the personalized content contained in a frame and displays the rendered web page and the frame to the user.
Abstract:
An online system obtains a composite prediction associated with a content item indicating a likelihood that a viewing user of the online system will perform a type of conversion associated with the content item via one or more paths of events leading to the type of conversion. The online system obtains the composite prediction based on a tree data structure describing the path(s) of events. Upon identifying an opportunity to present content to the viewing user, the online system identifies the tree data structure corresponding to the type of conversion from multiple tree data structures maintained in the online system and obtains a composite prediction associated with the content item by evaluating and performing operations associated with nodes of the tree data structure while traversing the nodes. The online system then determines whether to present the content item to the viewing user based on the composite prediction.
Abstract:
An online system presents different content items to different sets of users to evaluate how changes to content or changes to the online system affect user interaction with the content items or presentation of the content items. However, if the online system receives compensation for presenting different content items, the online system may receive a disproportionate amount of compensation for presenting one of the content items that improves user interaction. To prevent such disproportionate allocation of compensation between presentation of different contents items, the online system allocates sets of users to whom different content items are eligible to be presented to maintain a specified budget for presenting the different content items. The online system also differently allocates users across sets to whom different content items are eligible for presentation to prevent biasing of users from presentation of other different content items to users done in parallel.
Abstract:
An online advertising system stores advertisement placements and an advertisement campaign that is associated with the advertisement placements. The advertisement campaign includes a plurality of advertisement sets that each are associated with a respective set of selection rules. A request for an advertisement is received from a publishing system, the request specifying an advertisement placement and including advertisement selection information. The advertisement campaign is identified based in part on the advertisement placement, and an advertisement set is selected based in part on the selection information and a set of selection rules associated with the advertisement set. A creative group within the selected advertisement set is selected based on the selection rules, and an advertisement within the selected created group is selected using portions of the advertisement selection information and asset parameters associated with the advertisements in the selected creative group. The selected advertisement is provided to fill the advertisement placement.
Abstract:
Systems, methods, and non-transitory computer-readable media can determine an application feature causing an application to crash. A set of users is ranked based on application data. The application data comprises crash cause data indicative of the number of times the application feature caused the application to crash for a user. A high crash user group is determined based on the ranking the set of users. The application feature is disabled for the high crash user group. A subset of the high crash user group is periodically replaced with a set of new users not currently in the high crash user group.
Abstract:
A user device requests a web page from a web server of a third-party website, which is separate from a social networking system. The web server from the third-party website sends a markup language document for the requested web page to the user device which includes an instruction for a browser application running on the user device to incorporate information obtained from the social networking system within the web page. Based on the instruction in the received markup language document, the user device requests personalized content from the social networking system, which generates the requested personalized content based on social information about the user. The user device then renders the web page with the personalized content contained in a frame and displays the rendered web page and the frame to the user.
Abstract:
Systems, methods, and non-transitory computer-readable media can determine an application feature causing an application to crash. A set of users is ranked based on application data. The application data comprises crash cause data indicative of the number of times the application feature caused the application to crash for a user. A high crash user group is determined based on the ranking the set of users. The application feature is disabled for the high crash user group. A subset of the high crash user group is periodically replaced with a set of new users not currently in the high crash user group.
Abstract:
A user device requests a web page from a web server of a third-party website, which is separate from a social networking system. The web server from the third-party website sends a markup language document for the requested web page to the user device which includes an instruction for a browser application running on the user device to incorporate information obtained from the social networking system within the web page. Based on the instruction in the received markup language document, the user device requests personalized content from the social networking system, which generates the requested personalized content based on social information about the user. The user device then renders the web page with the personalized content contained in a frame and displays the rendered web page and the frame to the user.