Abstract:
An online system provides a feed of content including organic content items and sponsored content items that are positioned relative to each other to maximize user interaction with the feed of content. To reduce latency of providing the feed of content to a user without impairing positioning of organic content items and sponsored content items relative to each other, the online system initially selects a subset of sponsored content items based on characteristics (e.g., bid amounts) of the sponsored content items. Subsequently, the online system applies one or more selection processes to organic content items and to sponsored content items of the subset that accounts for positioning of sponsored content items and organic content items relative to each other within the feed of content. Hence, the online system evaluates the subset of sponsored content items along with organic content items when ordering content within the feed.
Abstract:
A social networking system dynamically adjusts a number of advertisements presented to a user along with organic content items by modifying a ranking including organic content items and advertisements. Partial engagement scores are generated for organic content items based on an expected amount of user interaction with each organic content item, and scores are generated for advertisements based on expected user interaction and bid amounts associated with each organic content item. An engagement score measuring the user's estimated interaction with a content feed including organic content items without advertisements and an additional engagement score measuring the user's estimated interaction with a content feed including organic content items and advertisements are determined from the partial engagement scores and the scores. A difference between the additional engagement score and the engagement score modifies a conversion factor used to combine expected user interaction and bid amounts to generate advertisement scores.
Abstract:
A social networking system dynamically adjusts a number of advertisements presented to a user along with organic content items by modifying a ranking including organic content items and advertisements. Partial engagement scores are generated for organic content items based on an expected amount of user interaction with each organic content item, and scores are generated for advertisements based on expected user interaction and bid amounts associated with each organic content item. An engagement score measuring the user's estimated interaction with a content feed including organic content items without advertisements and an additional engagement score measuring the user's estimated interaction with a content feed including organic content items and advertisements are determined from the partial engagement scores and the scores. A difference between the additional engagement score and the engagement score modifies a conversion factor used to combine expected user interaction and bid amounts to generate advertisement scores.
Abstract:
An online system accesses a content item containing a link to an external landing page. When an opportunity to present content to a viewing user occurs, the system determines a quality metric for the content item. The system further determines, based on the attributes of the external page, a quality metric for the external page. The quality metric for the external page is adjusted based on the quality metric of the content item. The system computes a value score for the content item based on the quality metrics for the content item and the external page. The content item is ranked against other content items for presentation in the opportunity. Content items are selected by the system and sent for presentation to the viewing user.
Abstract:
A social networking system dynamically adjusts a number of advertisements presented to a user along with organic content items by modifying a minimum bid amount associated with advertisements eligible for presentation to the user. Increasing the minimum bid amount decreases the number of advertisements presented to the user while decreasing the minimum bid amount increases the number of advertisements presented to the user. An engagement score measuring the user's estimated interaction with a content feed including organic content items without advertisements and an engagement score measuring the user's estimated interaction with a content feed including organic content items and advertisements are determined. A target score is determined based on the engagement scores, and a difference between the target score and a threshold value is used to modify a minimum price of advertisements eligible for presentation to the user.
Abstract:
An online system provides a feed of content including organic content items and sponsored content items that are positioned relative to each other to maximize user interaction with the feed of content. To reduce latency of providing the feed of content to a user without impairing positioning of organic content items and sponsored content items relative to each other, the online system initially selects a subset of sponsored content items based on characteristics (e.g., bid amounts) of the sponsored content items. Subsequently, the online system applies one or more selection processes to organic content items and to sponsored content items of the subset that accounts for positioning of sponsored content items and organic content items relative to each other within the feed of content. Hence, the online system evaluates the subset of sponsored content items along with organic content items when ordering content within the feed.
Abstract:
Methods and systems are described herein for predicting the quality of content items for display to a user of an online system. The method involves training a model to predict user values for content items based on ratings provided by a panel of professional raters for a set of content items. The trained model receives embeddings for a viewing user of the online system and for a page associated with a content item along with edge factors representing the viewing user's interactions on the online system and generates a user value representing the predicted quality of the content item for the viewing user. The method further involves combining the predicted user value with a user interaction score for the content item to generate a content item score used to determine whether to display the content item to the viewing user.
Abstract:
An online system receives requests from content providers to present content to a target user of the online system. A threshold value for the target user in an auction is determined based on historical auction data associated with the target user and only content items with maximum bid values greater than or equal to the threshold value can win an auction to present the content item to the target user. A winning candidate content item and a bid value for the winning content item are determined. The online system calculates a winning bid value based on a function of a total bid value of the second place candidate content item, an organic bid value of the winning content item and the threshold value determined for the target user. The content provider of the winning content item is charged the larger of the threshold value or the winning bid value.
Abstract:
An online system, such as a social networking system, displays a plurality of advertisements to users. The system selects an ad to display to a user based on a bidding system. The system receives feedback and user engagement data for an ad to compare the ad to other ads that are targeted to a similar group of users, to generate a relevance score. The relevance score can be provided to an advertiser as a way to quantify the effectiveness of the ad, and it reflects user engagement with the advertisement. In some embodiments, a projected relevance score can be calculated for a prospective advertisement by analyzing the content of the prospective ad prior to receiving user engagement data by comparing the prospective advertisement's content to other ads for which user engagement data does exist.
Abstract:
A social networking system presents content items, such as news feed stories and advertisements, to a user of the social networking system via a news feed. The social networking system determines to again present a content item via the news feed or to present a previously presented content item in a different position of the news feed. The social networking system identifies additional content items to present to the user as well as content items previously presented to the user. The social networking system scores the additional content items and the previously presented content items, accounting for a cost of removing the previously presented content item from its original position for presentation in the alternative position. Based on the score the social networking system ranks the content items selects, based on the rank, content items to present to the user.