Abstract: In one embodiment, a method includes identifying one or more social network events that satisfy a query condition in a social-networking system, determining an event score for each of the identified events, where the event score is based on one or more signals that are each related to a first interaction between a target user and the social-networking system, and the first interaction associates the target user with the identified event, and presenting one or more of the identified events to the target user in an order based on the event score of each identified event. The interaction may establish an association between the target user and an entity associated with the event.

Abstract: A social networking system identifies communications about an object associated with a brand owner. For each communication, the social networking system identifies users who were generated the communication, users who were exposed to the communication, and users who were not exposed to the communication. The social networking system determines a sentiment associated with a communication and may send a report based on the sentiment of the communications towards the brand owner. A request from a brand owner to present one or more response communications to users based on the users' relationship to a communication from a user about the object and the sentiment determined from the communication may be received by the social networking system. Based on the request, the social networking system presents a response communication to one or more users.

Abstract: In one embodiment, a method includes receiving, from beacons of a third-party (e.g., a business), session information for a user of an online social network. A mobile device of the user may have been in at least one wireless communication session with at least one beacon, and during the session the mobile device was proximate to the at least one beacon. The session information may include an identifier for the user, which may be used to access social-networking information for the user. Session information and the social-networking information of the user may be sent back to the third-party. User-specified permissions may delimit which information may be sent.

Abstract: In one embodiment, a social networking system maintains a moving average of the number of connection problems, including socket timeouts and failed uploads, per client in a geographic area to determine whether the wireless data network serving the geographic area is overloaded. In response to detecting a network overload, the social networking system may transmit an instruction to the clients in the particular geographic area to enter one of a plurality of traffic throttling modes. In particular embodiments, the social networking system maintains a historical log of network overload conditions, and uses the historical log to generate an estimate of the wireless network capacity serving a geographic area. Thus, the social networking system may preemptively transmit instructions to clients to enter a bandwidth-conservation mode when the estimated traffic demand exceeds the estimated capacity for a particular geographic region.

Abstract: The compatibility score of individuals in a social network is computed based on the compatibility of interests expressed by these individuals. The compatibility score between any two interests is calculated as the log of the estimated probability that a member of the social network will express both interests as his/her interests divided by the product of: (i) the estimated probability that a member of the social network will express the first of the two interests as his/her interest and (ii) the estimated probability that a member of the social network will express the second of the two interests as his/her interest. The compatibility score between two individuals is calculated as the sum of the compatibility scores between each interest appearing in a set of interests expressed by the first of the two individuals and each interest appearing in a set of interests expressed by the second of the two individuals.

Abstract: The compatibility score of individuals in a social network is computed based on the compatibility of interests expressed by these individuals. The compatibility score between any two interests is calculated as the log of the estimated probability that a member of the social network will express both interests as his or her interests divided by the product of: (i) the estimated probability that a member of the social network will express the first of the two interests as his or her interest and (ii) the estimated probability that a member of the social network will express the second of the two interests as his or her interest. The compatibility score between two individuals is calculated as the sum of the compatibility scores between each interest appearing in a set of interests expressed by the first of the two individuals and each interest appearing in a set of interests expressed by the second of the two individuals.

Abstract: In one embodiment, a method includes, by one or more computing systems, receiving, from a client system associated with a user, a request from the user for a content digest from an online social network, retrieving one or more content objects associated with the online social network that are accessible by the user, selecting one or more of the retrieved content objects to incorporate into the content digest based on their identified categories, generating one or more slides for the one or more selected content objects, respectively, wherein each slide comprises a summary and representative image of the respective selected content object, sending, to the client system of the user, instructions for presenting the content digest responsive to the request from the user, wherein the content digest comprises the one or more slides.

Abstract: To provide more contextually and temporally relevant information to its users, a social networking system may surface relevant information about a target user with whom an recipient user is likely to interact. The social networking system predicts whether the recipient user is likely to be in contact with a target user, either currently or in the near future. If contact is predicted, the system determines information about the target user that that the recipient user may find of interest for their interaction. To determine what information may be of interest, the system determines a relevance score for information items about that target user. The system can then use the relevance scores to decide whether and which information items to surface to the recipient user, e.g., in the form of notifications.

Abstract: A social networking system determines whether a user is a real public figure or is the correct “public persona” of an individual who is famous within a particular domain. The system selects one or more trusted agents. A trusted agent is a user who has been confirmed or is otherwise trusted within the system. The system traverses the social graph of the trusted agent to score and identify additional users who have a sufficient connection to the trusted agent to authenticate them as other confirmed public personas/figures. The system computes confidence scores of the connections of the trusted agent, considering the strength of the connections and other relevant factors. The system provides confidence scores for one or more target users in the social network based on the confidence scores of the friends or connections connecting the trusted agent and the target user.

Abstract: A social networking system allows a user to create an event in the social networking system while viewing a web page from a third-party website from a domain different than the social networking system. A widget or other social plug-in is included in the web page, and user interaction with the widget communicates information from the web page to the social networking system. An event object is created in the social networking system from the information from the web page. The social networking system may perform various actions to increase user interaction with the created event object, such as identifying additional users to invite the event or identifying users attending the event to other users.

Abstract: Method or system for allowing a social networking system to retain users of a social networking system by identifying low-activity users who are likely to become inactive/dormant users and prompting users to initiate interactions with the low-activity users. The low-activity users are identified by monitoring activities and interactions of the users via the social networking system. If the pattern of activities and interactions satisfy one or more criteria, a computer device for providing the social networking system initiates an intervention scheme where users are induced to initiate interactions with the low-activity users. In response to the interactions, the low-activity users are likely to resume interactions via the social networking system.

Abstract: In one embodiment, a method includes receiving content from a first user at a first time, determining whether one or more second users should be notified of the received content based on an associated first priority level, and sending a first notification to these second users. The first notification includes a subset of user-facing information of the received content. The method additionally includes receiving an update to the content from the first user at a second time which is later in time than the first time, determining whether one or more second users should be notified of the received update based on an associated second priority level, and sending a second notification to these second users. The second notification includes a second subset of the user-facing information associated with the received update.

Abstract: A social network contains information describing information about members of the social network and about various connections among the members. An external system that interacts with users (such as a website) communicates with the social network to access information about the members of the social network. In particular, the external system may determine whether a user is a member of the social network and then obtain information about the member and the member's connections within the social network. This allows an external system to use information from the social network to enhance a user's experience on the external system, while enforcing each member's privacy settings.

Abstract: In one embodiment, a method includes a device receiving a request to connect a minor with another user within a social-networking system. The minor and the user may be associated with a first and a second account, respectively. The device may identify the minor's guardian. A first approval request may be sent to the minor or the guardian to seek approval of the requested connection between the minor and the other user. The first approval request may be sent to the guardian upon determining that the request is initiated by the minor, or it may be sent to the minor upon determining that the request is initiated by the guardian. The device may send a second approval request to the other user to seek approval of the requested connection as well. When the requests are approved, a connection may then be established between the minor and the other user.

Abstract: A system and method for determining a trust level for a non-approved user in a social network is described. The method includes monitoring requests for social network interactions between an approved user and the non-approved user and determining if each interaction requested is of a first type or a second type. The method further includes increasing a first trust value when the interaction requested is of the first type and increasing a second trust value when the interaction requested is of the second type. The method further includes determining the trust level based on the first trust value and the second trust value. The method further includes changing the status of the non-approved user to an approved user based on the trust level, the first trust value and/or the second trust value.

Abstract: To suggest new connections to a user of a social networking system, the system generates a set of candidate users to whom the user has not already formed a connection. The system determines the likelihood that the user will connect to each candidate user if suggested to do so, and it also computes the value to the social networking system if the user does connect to the candidate user. Then, the system computes an expected value score for each candidate user based on the corresponding likelihood and the value. The candidate users are ranked and the suggestions are provided to the user based on the candidate users' expected value scores. The social networking system can suggest other actions to a user in addition to forming a new connection with other users.

Abstract: An online system reviews content for violation of one or more policies of the system. The system may evaluate various content policies to determine how usage of the policy affects user experience and what content is shown to each user. The system can, for example, run an A/B validation for certain policies, such as before launching a new policy. To enable the validation, when content is determined to be violating a policy, it is labeled with the specific policy violated as a shadow tag that is not visible to the user viewing the content. Then, the system may track user interactions with newsfeeds of content that include no policy violating content and newsfeeds that include some policy-violating content, and detect at a policy-by-policy level how each policy affects the newsfeed and user experience.

Abstract: Systems, methods, and non-transitory computer-readable media can generate a set of candidate content items from a plurality of content items that are available in the social networking system for a first user. A corresponding score for each of the candidate content items can be generated based at least in part on one or more social affinity coefficients corresponding to the first user and a respective second user associated with a candidate content item, wherein a social affinity coefficient provides a quantitative measurement of the strength of a relationship between two users. A first set of content items from the set of candidate content items can be determined based at least in part on the respective scores, wherein content items in the first set are included in a content feed provided to the first user.

Abstract: In one embodiment, a method includes receiving one or more input signals comprising one or more event signals associated with an event and one or more user signals associated with a user, where the input signals include time-based signals, each of which includes an event time or a user arrival time, and the input signals further include location-based signals, each of which includes an event location or a user location. The method may further include determining, using a trained machine-learning model, whether the user attended the event according to the input signals, and presenting, to a target user, an indication of whether the user attended the event. The machine-learning model may be trained on list of tuples, each of which includes a user identifier, an event identifier, and an indication of whether the user identified by the user identifier attended the event identified by the event identifier.

Abstract: Applications in social networks support interaction between members through various types of channels such as notifications, newsfeed, and so forth. For each channel, applications are ranked based on their user affinity measures. User affinity is based on measuring positive and negative interactions by users as both senders and recipients of messages generated by applications. Metrics are computed for the different types of messages and interactions provided by applications. For each channel, an application receives user affinity score based on specific weighted combination of the metrics. Applications use channel resources to send messages to increase their user base. Given the large number of applications that are available, the extent to which applications are allowed to use channels is controlled, limiting their resource consumption. User affinity scores of applications calculated for a channel are used to decide the allocation of channel resources for an application.