Abstract: To display a news feed in a social network environment, a social networking system generates news items regarding activities associated with a user of a social network environment. The social networking system may also attach an informational link associated with at least one of the activities to at least one of the news items, limit access to the news items to a predetermined set of viewers, and assign an order to the news items. The news items may be displayed in the assigned order to at least one viewing user of the predetermined set of viewers, and the number of news items displayed may be dynamically limited.

Abstract: A system, method, and computer program for social mapping is provided. Data about a plurality of social network members is received. A first member of the plurality of social network members is allowed to identify a second member of the plurality of social network members with whom the first member wishes to establish a relationship. The data is then sent to the second member about the first member based on the identification. Input from the second member is received in response to the data. The relationship between the first member and the second member is confirmed based on the input in order to map the first member to the second member.

Abstract: To display a news feed in a social network environment, a social networking system generates news items regarding activities associated with a user of a social network environment. The social networking system may also attach an informational link associated with at least one of the activities to at least one of the news items, limit access to the news items to a predetermined set of viewers, and assign an order to the news items. The news items may be displayed in the assigned order to at least one viewing user of the predetermined set of viewers, and the number of news items displayed may be dynamically limited.

Abstract: A social networking system manages the accessibility of content items provided by users and directed to various audiences in the social networking system. An author provides the social networking system with a content item, a content item tag indicating an association between the content item and a tagged user, and a definition of a first audience who may view the content item. The social networking system then allows the tagged user to provide a definition of a second audience who may view the content item, where the second audience may contains users who are not in the first audience defined by the original author. The social networking system then determines whether a viewing user may view the posted content item (and tag) based on whether the viewing user is in at least one of the first audience and the second audience.

Abstract: A system, method, and computer program for social mapping is provided. Data about a plurality of social network members is received. A first member of the plurality of social network members is allowed to identify a second member of the plurality of social network members with whom the first member wishes to establish a relationship. The data is then sent to the second member about the first member based on the identification. Input from the second member is received in response to the data. The relationship between the first member and the second member is confirmed based on the input in order to map the first member to the second member.

Abstract: A social networking service presents information about the social network using multiple feeds in a user interface and provides mechanisms for filtering the content. A content feed includes the most recent content generated by the user's connections, and a highlights feed displays content based on importance and relevance. A user may add content to the social networking service through a composer interface. A user may also filter either or both of the content feed and the highlights feed using a filtering interface, which allows selective filtering of the feeds using one or more different types of filters, including as filtering by the source of the content, friends or networks, and/or content type.

Abstract: A social networking service presents information about the social network using multiple feeds in a user interface and provides mechanisms for filtering the content. A content feed includes the most recent content generated by the user's connections, and a highlights feed displays content based on importance and relevance. A user may add content to the social networking service through a composer interface. A user may also filter either or both of the content feed and the highlights feed using a filtering interface, which allows selective filtering of the feeds using one or more different types of filters, including as filtering by the source of the content, friends or networks, and/or content type.

Abstract: In one embodiment, a method includes accessing a social graph that includes a plurality of nodes and edges, identifying a nodes corresponding to a page currently accessed by a first user, generating one or more structured queries, where each structured query comprises a reference to the identified node and one or more edges that are connected to the identified node, and transmitting one or more of the structured queries to the first user for display on the page.

Abstract: A system, method, and computer program for generating a social timeline is provided. A plurality of data items associated with at least one relationship between users associated with a social network is received, each data item having an associated time. The data items are ordered according to the at least one relationship. A social timeline is generated according to the ordered data items.

Abstract: In one embodiment, a method includes accessing a social graph that includes a plurality of nodes and edges, identifying a nodes corresponding to a page currently accessed by a first user, generating one or more structured queries, where each structured query comprises a reference to the identified node and one or more edges that are connected to the identified node, and transmitting one or more of the structured queries to the first user for display on the page.

Abstract: A social networking system manages the accessibility of content items provided by users and directed to various audiences in the social networking system. An author provides the social networking system with a content item, a content item tag indicating an association between the content item and a tagged user, and a definition of a first audience who may view the content item. The social networking system then allows the tagged user to provide a definition of a second audience who may view the content item, where the second audience may contains users who are not in the first audience defined by the original author. The social networking system then determines whether a viewing user may view the posted content item (and tag) based on whether the viewing user is in at least one of the first audience and the second audience.

Abstract: A social graph may be modeled as a collection of claims. Each claim is associated with an author, an audience, and an assertion about a fact. Probabilistic information may be collected from various sources for a claim, enabling a social networking system to evaluate a truthfulness of the assertion made in the claim. User-declared profile information may be evaluated as claims. A user, entity, or application may make claims about any assertions made in the social networking system. Reputation scores may be determined for users based on evaluations of their historical assertions. Claims may be evaluated for truthfulness using a probabilistic prediction model using heuristics analysis, regression analysis, and machine learning methods. A claims-based profile of users may be provided to viewers based on the contexts in which the claims were made. Viewers may view claims made about users, such as the users' biographical information, contact information, expertise, and interests.

Abstract: A social networking system manages the accessibility of content items provided by users and directed to various audiences in the social networking system. An author provides the social networking system with a content item, a content item tag indicating an association between the content item and a tagged user, and a definition of a first audience who may view the content item. The social networking system then allows the tagged user to provide a definition of a second audience who may view the content item, where the second audience may contains users who are not in the first audience defined by the original author. The social networking system then determines whether a viewing user may view the posted content item (and tag) based on whether the viewing user is in at least one of the first audience and the second audience.

Abstract: A system, method, and computer program for generating a social timeline is provided. A plurality of data items associated with at least one relationship between users associated with a social network is received, each data item having an associated time. The data items are ordered according to the at least one relationship. A social timeline is generated according to the ordered data items.

Abstract: A system, method, and computer program for generating a social timeline is provided. A plurality of data items associated with at least one relationship between users associated with a social network is received, each data item having an associated time. The data items are ordered according to the at least one relationship. A social timeline is generated according to the ordered data items.

Abstract: A social graph may be modeled as a collection of claims. Each claim is associated with an author, an audience, and an assertion about a fact. Probabilistic information may be collected from various sources for a claim, enabling a social networking system to evaluate a truthfulness of the assertion made in the claim. User-declared profile information may be evaluated as claims. A user, entity, or application may make claims about any assertions made in the social networking system. Reputation scores may be determined for users based on evaluations of their historical assertions. Claims may be evaluated for truthfulness using a probabilistic prediction model using heuristics analysis, regression analysis, and machine learning methods. A claims-based profile of users may be provided to viewers based on the contexts in which the claims were made. Viewers may view claims made about users, such as the users' biographical information, contact information, expertise, and interests.

Abstract: A social graph may be modeled as a collection of claims. Each claim is associated with an author, an audience, and an assertion about a fact. Probabilistic information may be collected from various sources for a claim, enabling a social networking system to evaluate a truthfulness of the assertion made in the claim. User-declared profile information may be evaluated as claims. A user, entity, or application may make claims about any assertions made in the social networking system. Reputation scores may be determined for users based on evaluations of their historical assertions. Claims may be evaluated for truthfulness using a probabilistic prediction model using heuristics analysis, regression analysis, and machine learning methods. A claims-based profile of users may be provided to viewers based on the contexts in which the claims were made. Viewers may view claims made about users, such as the users' biographical information, contact information, expertise, and interests.

Abstract: A social graph may be modeled as a collection of claims. Each claim is associated with an author, an audience, and an assertion about a fact. Probabilistic information may be collected from various sources for a claim, enabling a social networking system to evaluate a truthfulness of the assertion made in the claim. User-declared profile information may be evaluated as claims. A user, entity, or application may make claims about any assertions made in the social networking system. Reputation scores may be determined for users based on evaluations of their historical assertions. Claims may be evaluated for truthfulness using a probabilistic prediction model using heuristics analysis, regression analysis, and machine learning methods. A claims-based profile of users may be provided to viewers based on the contexts in which the claims were made. Viewers may view claims made about users, such as the users' biographical information, contact information, expertise, and interests.

Abstract: A social graph may be modeled as a collection of claims. Each claim is associated with an author, an audience, and an assertion about a fact. Probabilistic information may be collected from various sources for a claim, enabling a social networking system to evaluate a truthfulness of the assertion made in the claim. User-declared profile information may be evaluated as claims. A user, entity, or application may make claims about any assertions made in the social networking system. Reputation scores may be determined for users based on evaluations of their historical assertions. Claims may be evaluated for truthfulness using a probabilistic prediction model using heuristics analysis, regression analysis, and machine learning methods. A claims based profile of users may be provided to viewers based on the contexts in which the claims were made. Viewers may view claims made about users, such as the users' biographical information, contact information, expertise, and interests.

Abstract: A social graph may be modeled as a collection of claims. Each claim is associated with an author, an audience, and an assertion about a fact. Probabilistic information may be collected from various sources for a claim, enabling a social networking system to evaluate a truthfulness of the assertion made in the claim. User-declared profile information may be evaluated as claims. A user, entity, or application may make claims about any assertions made in the social networking system. Reputation scores may be determined for users based on evaluations of their historical assertions. Claims may be evaluated for truthfulness using a probabilistic prediction model using heuristics analysis, regression analysis, and machine learning methods. A claims-based profile of users may be provided to viewers based on the contexts in which the claims were made. Viewers may view claims made about users, such as the users' biographical information, contact information, expertise, and interests.