Abstract: Disclosed herein is a statistical approach, a win share approach, used to assign a win share value to content items. User interaction with content items is tracked, and a win share value is assigned to content items in response to a “winning” action performed by a user. Win shares associated with content items are used to identify content items that are to be presented, and can further be used to identify an optimal presentation, e.g., layout, presentation frequency, etc., of content items that is to be presented.

Abstract: Techniques introduced here include a system and method for determining whether to provide a user of a social networking system with candidate users (i.e., potential contacts) with whom the user does not already have any connections with. In some embodiments, the system generates a set of candidate users based on a value (e.g., to the social networking system) associated with each potential connection formed between the user and the set of candidate users. In one or more embodiments, the system ranks the candidate users based on their connection-value to the social networking system and provides the ranked candidate users as suggested new connections to the user.

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: 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: Disclosed herein is a statistical approach, a win share approach, used to assign a win share value to content items. User interaction with content items is tracked, and a win share value is assigned to content items in response to a “winning” action performed by a user. Win shares associated with content items are used to identify content items that are to be presented, and can further be used to identify an optimal presentation, e.g., layout, presentation frequency, etc., of content items that is to be presented.

Abstract: Disclosed herein is a statistical approach, a win share approach, used to assign a win share value to content items. User interaction with content items is tracked, and a win share value is assigned to content items in response to a “winning” action performed by a user. Win shares associated with content items are used to identify content items that are to be presented, and can further be used to identify an optimal presentation, e.g., layout, presentation frequency, etc., of content items that is to be presented.

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: Techniques introduced here include a system and method for determining whether to provide a user of a social networking system with candidate users (i.e., potential contacts) with whom the user does not already have any connections with. In some embodiments, the system generates a set of candidate users based on a value (e.g., to the social networking system) associated with each potential connection formed between the user and the set of candidate users. In one or more embodiments, the system ranks the candidate users based on their connection-value to the social networking system and provides the ranked candidate users as suggested new connections to the user.

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: 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: Apparatuses, methods, and systems directed to detect Internet bots in communication networks. Some embodiments of the present invention allow an agent of a server to periodically record interaction events on a client system. The recorded interaction events are sent to a server and validated by a statistical test. Some embodiments of the present invention may be used to detect bots using server logs. In other embodiments, an agent of a server is able to detect and validate interaction events on a client system and the server periodically polls the agent to determine whether bots are detected on the client system.

Abstract: Methods, apparatuses and systems directed to generating heat maps that facilitate analysis of user activity. In particular embodiments, a heat map represents activity intensity of time-based cohort groups over time.

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: The subject matter disclosed herein relates to simulation of bucket testing. In a particular implementation, cohort of users associated with a value for an engagement metric may be selected based at least in part on an intersection of first and second probability distributions. Behavior of the first and second groups may be compared based at least in part on the selected cohort of users.

Abstract: Apparatuses, methods, and systems directed to detect Internet bots in communication networks. Some embodiments of the present invention allow an agent of a server to periodically record interaction events on a client system. The recorded interaction events are sent to a server and validated by a statistical test. Some embodiments of the present invention may be used to detect bots using server logs. In other embodiments, an agent of a server is able to detect and validate interaction events on a client system and the server periodically polls the agent to determine whether bots are detected on the client system.

Abstract: The subject matter disclosed herein relates to simulation of bucket testing.

Abstract: Disclosed herein is a statistical approach, a win share approach, used to assign a win share value to content items. User interaction with content items is tracked, and a win share value is assigned to content items in response to a “winning” action performed by a user. Win shares associated with content items are used to identify content items that are to be presented, and can further be used to identify an optimal presentation, e.g., layout, presentation frequency, etc., of content items that is to be presented.

Abstract: Techniques are described herein for an automatic discovery and validation analyzer that identifies factors that have a particular effect on members of a population in engaging in certain activities. A baseline set and a divergent set of members of the population are identified based on whether a member has experienced a significant change in magnitude of the particular effect during a particular period of time. Differences in behaviors of members of the baseline and divergent sets are then analyzed to identify a candidate factor that corresponds to exposure to an item. Such a candidate factor is then validated as to whether it is a cause of said significant change in magnitude of the particular effect experienced by the divergent set of members.