Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for generating personalized insights. An insight generation system, in response to a first user of an online service having added a second user as a recipient of a message, gathers profile data of the second user and profile data of an entity that is maintained by the online service. The insight generation system determines a set of insights for the second user, based on the profile data of the second user, the profile data of the entity, and a set of insight algorithms. Each insight indicates commonalities between the second user and the entity. The insight generation system selects a subset of the set of insights, yielding a set of recommended insights, and provides the set of recommended insights to a client device of the first user.

Abstract: An online architecture includes various applications and platforms for determining metrics related to one or more electronic communications sent between members of an online service. The online architecture includes one or more front-end application(s) configured to provide one or more web page(s) or other graphical user interfaces for interacting with the disclosed systems and architecture. The online architecture also includes a stream processing platform and a distributed processing platform, where the stream processing platform handles volatile information and the distributed processing platform handles less volatile information. The stream processing platform and the distributed processing platform modify event records corresponding to the electronic messages. The event records are correlated to determine one or more metrics related to the one or more electronic communications.

Abstract: A system and method includes obtaining, for a population of users of an online networking system having a common profession, data related to factors pertaining to the profession from a database of the online networking system and successively, for each of the factors individually, removing from the population of users those whose data relating to the factor is not similar to related data of a subject user until a quantity of the population of users is within a predetermined range to obtain a comparable population of users that have similar data to the subject user. A statistic is compared from the data of the subject user against the same statistic from the data of each of the users of the comparable population of users to obtain a comparison. The user interface displays the statistic and information related to the comparison.

Abstract: In an embodiment, a system accesses a candidate stream definition comprising a hiring organization and a role. Additionally, the system accesses, based on the candidate stream definition, one or more stream-related information sources, the stream-related information sources including member profiles of members of an online system. Moreover, the system causes presentation, on a display device, of one or more of the member profiles, the presentation including, for each of the one or more of the member profiles, a user interface element selectable to send a message to a member of the online system. Furthermore, in response to receiving a selection of the user interface element for a member of the one or more of the member profiles, the system populates a message template based on features of the hiring organization and the role. The system also sends a message including the message template to a member of the member profile.

Abstract: Systems and methods for improving search results using social routing are provided. In example embodiments, an affinity metric and match metric are determined for a plurality of users. The affinity metric indicates an interaction level between a given user and the match metric indicates how well the given user matches parameters of a search string. Based on a correlation between the affinity metric and the match metric, one or more items of content may be transmitted to one or more selected users. Improved search results can then be generated based on interactions with the one or more items of content.

Abstract: Systems and methods for improving search results using assessment based routing are provided. In example embodiments, social network data for members in an organization and members outside the organization is accessed. An internal member and external member may share one or more attributes, such as working on the same project or within the same company. An electronic assessment can be sent to the internal member to generate assessment data about the external member. The assessment data can be included in an electronic message sent to the external member. Interaction data from the electronic message can be received when the external member opens and interacts with the electronic message.

Abstract: Systems and methods for improving search results using social routing are provided. In example embodiments, an affinity metric and match metric are determined for a plurality of users. The affinity metric indicates an interaction level between a given user and the match metric indicates how well the given user matches parameters of a search string. Based on a correlation between the affinity metric and the match metric, one or more items of content may be transmitted to one or more selected users. Improved search results can then be generated based on interactions with the one or more items of content.

Abstract: Systems and methods for improving search results using assessment based routing are provided. In example embodiments, social network data for members in an organization and members outside the organization is accessed. An internal member and external member may share one or more attributes, such as working on the same project or within the same company. An electronic assessment can be sent to the internal member to generate assessment data about the external member. The assessment data can be included in an electronic message sent to the external member. Interaction data from the electronic message can be received when the external member opens and interacts with the electronic message.

Abstract: In an example embodiment, a supervised machine learning algorithm is used to train a communication reply score model based on an extracted first set of features and second set of features from social networking service member profiles and activity and usage information. When a plurality of member search results is to be displayed, for the member identified in each of the plurality of member search results, the member profile corresponding to the member is parsed to extract a third set of one or more features from the member profile, activity and usage information pertaining to actions taken by the members on the social networking service is parsed to extract a fourth set of one or more features, and the extracted third set of features and fourth set of features is inputted into the communication reply score model to generate a communication reply score, which is displayed visually to a searcher.

Abstract: In an example embodiment, a supervised machine learning algorithm is used to train a communication reply score model based on an extracted first set of features and second set of features from social networking service member profiles and activity and usage information. When a plurality of member search results is to be displayed, for the member identified in each of the plurality of member search results, the member profile corresponding to the member is parsed to extract a third set of one or more features from the member profile, activity and usage information pertaining to actions taken by the members on the social networking service is parsed to extract a fourth set of one or more features, and the extracted third set of features and fourth set of features is inputted into the communication reply score model to generate a communication reply score, which is displayed visually to a searcher.