Abstract: Systems, methods, and non-transitory computer-readable media can determine a profile model for a page that is accessible through the social networking system, the profile model describing one or more modal characteristics of users of the social networking system that have fanned the page. A determination can be made that the page should be recommended to a first user of the social networking system based at least in part on the profile model. At least one page recommendation that references the page can be provided to the first user.

Abstract: Systems, methods, and non-transitory computer-readable media can determine a content item to be promoted to one or more users of the social networking system. At least one seed content item in the social networking system that is similar to the content item to be promoted can be determined. A set of interests can be determined based at least in part on the at least one seed content item. One or more interests in the set can be determined as suggestions for promoting the content item to users, wherein promoting the content item using a first interest causes the content item to be presented to users of the social networking system that are associated with the first interest.

Abstract: Systems, methods, and non-transitory computer-readable media can determine respective geographic locations of a set of users associated with a page that is accessible through a social network. At least one centroid for the page can be generated based at least in part on the respective geographic locations of the set of users. At least one area of influence of the page can be determined based at least in part on the centroid.

Abstract: A social networking system recommends objects, such as pages, of the social networking system to users of the social networking system based on the location of the user. The social networking system obtains location information identifying the location of the user. Based on the location of the user, the social networking system identifies levels of geographical partitions encompassing the location of the user. For each level of geographical partitions, the social networking system accesses relevant objects of the social networking system with connections to users located within the level of geographical partitions. The social networking system may have determined a term frequency-inverse document frequency (tf-idf) value for each relevant object. Based on the number of connections and the tf-idf value associated with each relevant object, the social networking system merges the relevant objects accessed at each level into a set of relevant objects to recommend to the user.

Abstract: A social networking system recommends objects, such as pages, of the social networking system to users of the social networking system based on the location of the user. The social networking system obtains location information identifying the location of the user. Based on the location of the user, the social networking system identifies levels of geographical partitions encompassing the location of the user. For each level of geographical partitions, the social networking system accesses relevant objects of the social networking system with connections to users located within the level of geographical partitions. The social networking system may have determined a term frequency-inverse document frequency (tf-idf) value for each relevant object. Based on the number of connections and the tf-idf value associated with each relevant object, the social networking system merges the relevant objects accessed at each level into a set of relevant objects to recommend to the user.

Abstract: Systems, methods, and non-transitory computer readable media configured to determine features based on online user behavior regarding a seed content item and a candidate content item that may be presented in response to an indication of approval by a user regarding the seed content item. The features are processed to generate a probability that the user will interact with the candidate content item. The candidate content item is selected for presentation to the user based on the probability that the user will interact with the candidate content item.

Abstract: Systems, methods, and non-transitory computer readable media configured to determine seed content items based on interests of a user. Candidate content items can be determined for potential presentation to the user based at least in part on the seed content items. Features associated with the candidate content items can be processed to generate probabilities that the user will perform interactions with the candidate content items. Values can be assigned to the candidate content items based on the probabilities that the user will perform interactions with the candidate content items and the importance of the interactions. The values can be provided as bid values to an auction system to determine constraints regarding presentation of the candidate content items. Presentation of the candidate content items can be optimized.

Abstract: The social networking system monitors implicit interactions between a user and objects of the social networking system with which the user has not established a connection. Based on the implicit interactions between the user and an object, the social networking system identifies a soft connection between the user and the object. The social networking system may then identify soft connections to include in a candidate list of soft connections to recommend to the user. The social networking system may also extract signals from the set of candidate list of soft connections, and may use the extracted signals to rank the soft connections in the list of candidate soft connections. The social networking system may then recommend soft connections to the user based on the rank associated with the soft connections in the candidate list of soft connections.

Abstract: A social networking system recommends objects, such as pages, of the social networking system to users of the social networking system based on the location of the user. The social networking system obtains location information identifying the location of the user. Based on the location of the user, the social networking system identifies levels of geographical partitions encompassing the location of the user. For each level of geographical partitions, the social networking system accesses relevant objects of the social networking system with connections to users located within the level of geographical partitions. The social networking system may have determined a term frequency-inverse document frequency (tf-idf) value for each relevant object. Based on the number of connections and the tf-idf value associated with each relevant object, the social networking system merges the relevant objects accessed at each level into a set of relevant objects to recommend to the user.

Abstract: A method and system for determining the importance of news events based on news reports published by news sources on news home pages is provided. A news system identifies news home pages that contain references to news reports on detail pages. The news system calculates the importance of a news event based on the importance of news reports reporting that news event. The news system may determine the importance of a news report based on the assumption that the importance of a news report is based on the credibility of news home pages and the importance of similar news reports. The news system may recursively define the importance of a news report based on the credibility of news home pages and the similarity to other news pages and the importance of a news home page based on the importance of its news reports and similar news reports.

Abstract: A method and system for determining the importance of news events based on news reports published by news sources on news home pages is provided. A news system identifies news home pages that contain references to news reports on detail pages. The news system calculates the importance of a news event based on the importance of news reports reporting that news event. The news system may determine the importance of a news report based on the assumption that the importance of a news report is based on the credibility of news home pages and the importance of similar news reports. The news system may recursively define the importance of a news report based on the credibility of news home pages and the similarity to other news pages and the importance of a news home page based on the importance of its news reports and similar news reports.