Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a count of actions associated with a member of a social network, wherein the count comprises a set of action types and a number of actions associated with the member for each of the action types. Next, the system uses the count to calculate a set of scores for measuring the value of the social network to the member, wherein the set of scores is associated with researching and contacting people, building a network, keeping up with connections, staying informed and building knowledge, establishing and managing a reputation, and getting hired. The system then outputs the scores for use in characterizing and improving the value of the social network for the member.

Abstract: System and techniques for activity sensing online preference assay are described herein. An initial indication of an online activity preference for a member of a social network service may be obtained. A plurality of member activities corresponding with the online activity preference for a period of time subsequent to obtaining the initial indication may be collected. Respective decision trees of a set of decision trees may be traversed based on a set of inputs comprising the collected plurality of member activities to determine a probability that the online activity preference corresponds with the member. An actual online activity preference may be derived for the member using an aggregation of the determined probability for the respective decision trees of the set of decision trees. Social network content items may be filtered for the member based on the actual online activity preference.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a count of actions associated with a member of a social network, wherein the count comprises a set of action types and a number of actions associated with the member for each of the action types. Next, the system uses the count to calculate a set of scores for measuring the value of the social network to the member, wherein the set of scores is associated with researching and contacting people, building a network, keeping up with connections, staying informed and building knowledge, establishing and managing a reputation, and getting hired. The system then outputs the scores for use in characterizing and improving the value of the social network for the member.

Abstract: A system determines an intent of a current user who is interacting with an online social networking system, and requests information from the current user based on the determined intent of the current user. The system then receives the requested information from the current user, and provides a service or information to the current user based on the intent of the current user and the information provided by the current user.

Abstract: System and techniques for activity sensing online preference assay are described herein. An initial indication of an online activity preference for a member of a social network service may be obtained. A plurality of member activities corresponding with the online activity preference for a period of time subsequent to obtaining the initial indication may be collected. Respective decision trees of a set of decision trees may be traversed based on a set of inputs comprising the collected plurality of member activities to determine a probability that the online activity preference corresponds with the member. An actual online activity preference may be derived for the member using an aggregation of the determined probability for the respective decision trees of the set of decision trees.

Abstract: System and techniques for activity sensing online preference assay are described herein. A count for an action completed by a member of a social network service may be detected over a first period of time. The member may be labeled with an online activity preference based on the count and a subset of the first period of time. A plurality of member activities corresponding with the online activity preference may be collected for a second period of time prior to obtaining the initial indication. Respective decision trees of a set of decision trees may be traversed based on a set of inputs comprising the collected plurality of member activities to determine a probability that the online activity preference corresponds with the member. An actual online activity preference may be derived for the member using an aggregation of the determined probability for the respective decision trees of the set of decision trees.