Abstract:
The present disclosure is directed toward systems and methods for dynamically providing digital content to client devices at different insertion points of a digital video based on predicted total value of inserting the digital content and predicted engagement loss of inserting the digital content. For example, system and methods described herein determine that an insertion point is approaching in an actively playing digital video. In response, systems and methods identify digital content for insertion at the insertion point. In one or more embodiments, the described systems and methods insert the identified digital content by comparing the predicted total value of inserting the digital content at the insertion point of the digital video and a predicted engagement loss associated with inserting the digital content at the insertion point of the digital video.
Abstract:
The present disclosure is directed toward systems and methods for dynamically providing digital content to client devices at different insertion points of a digital video based on predicted total value of inserting the digital content and predicted engagement loss of inserting the digital content. For example, system and methods described herein determine that an insertion point is approaching in an actively playing digital video. In response, systems and methods identify digital content for insertion at the insertion point. In one or more embodiments, the described systems and methods insert the identified digital content by comparing the predicted total value of inserting the digital content at the insertion point of the digital video and a predicted engagement loss associated with inserting the digital content at the insertion point of the digital video.
Abstract:
An online system receives a request for a video to be presented by the online system to a target user. The online system determines whether to insert secondary content into the video. For such a determination, the online system identifies a position in the video for inserting secondary content. Further, the online system determines a loss score and a gain score. The loss score measures a loss of interaction by the target user if the secondary content were inserted. The gain score includes a monetary compensation to be received by the online system for inserting the secondary content at the identified position. The online system compares the loss score and the gain score. Based on the gain score offsetting the loss score, the online systems modifies the video by inserting the secondary content at the identified position and provides the modified video for display to the target user.
Abstract:
An online system receives a request for a video to be presented by the online system to a target user. The online system determines whether to insert secondary content into the video. For such a determination, the online system identifies a position in the video for inserting secondary content. Further, the online system determines a loss score and a gain score. The loss score measures a loss of interaction by the target user if the secondary content were inserted. The gain score includes a monetary compensation to be received by the online system for inserting the secondary content at the identified position. The online system compares the loss score and the gain score. Based on the gain score offsetting the loss score, the online systems modifies the video by inserting the secondary content at the identified position and provides the modified video for display to the target user.
Abstract:
An online system applies content policies regulating presentation of sponsored content to its users. For example, content policies may prevent the presentation of sponsored content items in certain positions content feeds. The online system may relax a content policy when generating a content feed for a user based on characteristics of a user. For example, the online system generates a model determining a tolerance of the user for sponsored content, and relaxes one or more content policies if the tolerance of the user for sponsored content equals or exceeds a threshold. As another example, the online system determines whether to relax one or more content policies based on a comparison of a historical amount of compensation received from the user and an expected amount of compensation from presenting content items violating a content policy.
Abstract:
An online system applies content policies regulating presentation of sponsored content to its users. For example, content policies may prevent the presentation of sponsored content items in certain positions content feeds. The online system may relax a content policy when generating a content feed for a user based on characteristics of a user. For example, the online system generates a model determining a tolerance of the user for sponsored content, and relaxes one or more content policies if the tolerance of the user for sponsored content equals or exceeds a threshold. As another example, the online system determines whether to relax one or more content policies based on a comparison of a historical amount of compensation received from the user and an expected amount of compensation from presenting content items violating a content policy.
Abstract:
An online system receives advertisement (“ad”) requests for presentation to online system users. An ad request may include an identifier of a landing page identifying a source external to the online system from which content is retrieved and presented to a user who interacts with content from the ad request. The online system determines a quality score for the source based on a frequency with which online system users request content from the source via the online system and various types of interactions by online system users with content associated with the source that is presented by the online system (e.g., interactions with content associated with the source indicating user interest in the source). Based on the quality score for the source, the online system modifies a score for the ad request used by the online system to determine whether to present content form the ad request to a user.
Abstract:
An online system selects content items for presentation to viewing users of the online system based on a composite score associated with each content item that includes a quality component and a revenue component. The revenue component is based on a monetary amount an advertiser associated with the content item is willing to pay for each interaction with the content item by a prospective viewing user, while the quality component indicates the quality of the content item to the prospective viewing user. The quality component is predicted based on explicit user quality ratings received from viewing users for various content items previously presented to the viewing users, in which the viewing users have at least a threshold measure of similarity to the prospective viewing user and/or the various content items rated by the viewing users have at least a threshold measure of similarity to the content item being scored.
Abstract:
A social networking system presents a content feed including organic content items and sponsored content items to a user. To maintain user interaction with the content feed, the social networking system determines probabilities of the user performing various types of interactions with a sponsored content item and accounts for the determined probabilities when selecting content items for presentation via the content feed. For example, the social networking system generates a value for the sponsored content item based on the determined probabilities and determines a score for the sponsored content item based on the value and a bid amount associated with the sponsored content item. When selecting content for the content feed, the social networking system evaluates the sponsored content item based on its associated score. Prior interactions between the user and previously presented content may be used when determining the score for the sponsored content item.
Abstract:
A social networking system selects content items for presentation to a user. To promote user interaction with selected content items, the social networking system scores content items based at least in part on similarity in appearances of the content items to an appearance of a content item for which the social networking system is compensated for presentation (a “sponsored content item”). For example, a model is applied to features describing appearance of a content item to generate the score for a content item. When selecting content items for presentation, a score associated with a content item may modify the likelihood of the content item being selected. A content item with a score indicating greater than a threshold similarity in appearance to an appearance of a sponsored content item may be penalized when the social networking system selects content for presentation.