Abstract: Methods and systems for tracking sources of after-hours activity based on events managed via an electronic communication application. One method includes accessing a log storing time information, receiver information, and originator information of an event managed via the electronic communication application, determining, based on the receiver information, a predetermined after-hours period of a receiver of the event, determining, based on the originator information and stored organizational data, an organizational group of an originator of the event, and determining, based on the time information, whether the event occurred during the predetermined after-hours period of the receiver.

Abstract: Methods and systems for tracking sources of after-hours activity based on events managed via an electronic communication application. One method includes accessing a log storing time information, receiver information, and originator information of an event managed via the electronic communication application, determining, based on the receiver information, a predetermined after-hours period of a receiver of the event, determining, based on the originator information and stored organizational data, an organizational group of an originator of the event, and determining, based on the time information, whether the event occurred during the predetermined after-hours period of the receiver.

Abstract: A system and method for identifying a user is described. The system identifies collaboration metrics based on user interaction data of users of an application from an enterprise. The system accesses enterprise organizational data of the enterprise and identifies topic data from the user interaction data and the enterprise organizational data. The system trains a machine learning model based on the collaboration metrics, the enterprise organizational data, and the topic data.

Abstract: Methods and systems for tracking sources of after-hours activity based on events managed via an electronic communication application. One method includes accessing a log storing time information, receiver information, and originator information of an event managed via the electronic communication application, determining, based on the receiver information, a predetermined after-hours period of a receiver of the event, determining, based on the originator information and stored organizational data, an organizational group of an originator of the event, and determining, based on the time information, whether the event occurred during the predetermined after-hours period of the receiver.

Abstract: A system and method for identifying a user is described. The system identifies collaboration metrics based on user interaction data of users of an application from an enterprise. The system accesses enterprise organizational data of the enterprise and identifies topic data from the user interaction data and the enterprise organizational data. The system trains a machine learning model based on the collaboration metrics, the enterprise organizational data, and the topic data.

Abstract: A system and method for configuring an application is described. The system identifies user collaboration data of users of an application. The user collaboration data indicates durations of collaborations between one or more users using the application. The system computes an influencer score of a first user based on the duration of collaborations between the first user and the other users. The system determines that the influencer score of the first user exceeds an influencer score threshold and generates a configuration setting of the application for the first user. The system applies the configuration setting to the application for the first user.

Abstract: A system and method for identifying a user is described. The system identifies collaboration metrics based on user interaction data of users of an application from an enterprise. The system accesses enterprise organizational data of the enterprise and identifies topic data from the user interaction data and the enterprise organizational data. The system trains a machine learning model based on the collaboration metrics, the enterprise organizational data, and the topic data.

Abstract: A method may include presenting a graphical user interface (GUI) configured to define a network for analysis, the GUI including: a first portion configured to define a network boundary of an organizational network graph (ONG) in a dataset; a second portion configured to define a beginning time and ending time for the network analysis; and a third portion configured to define a set of one or more graph metrics for vertices in the ONG; retrieving a portion of the dataset based on the network boundary, beginning time, and ending time; transmitting instructions to a distributed computing platform to generate the set of graph metrics on the portion of the dataset; and storing the generated set of graph metrics as associated with the network analysis.

Abstract: A method may include presenting a graphical user interface (GUI) configured to define a network for analysis, the GUI including: a first portion configured to define a network boundary of an organizational network graph (ONG) in a dataset; a second portion configured to define a beginning time and ending time for the network analysis; and a third portion configured to define a set of one or more graph metrics for vertices in the ONG; retrieving a portion of the dataset based on the network boundary, beginning time, and ending time; transmitting instructions to a distributed computing platform to generate the set of graph metrics on the portion of the dataset; and storing the generated set of graph metrics as associated with the network analysis.

Abstract: A novel, advanced polymeric swab is disclosed herein. The swabs have a surface texture that allows for independent motion between microscale regions, are reusable with no loss of accuracy or efficiency, and are fabricated from optoelectronically-active elements to minimize static charging during repeated use.

Abstract: A novel, advanced polymeric swab is disclosed herein. The swabs have a surface texture that allows for independent motion between microscale regions, are reusable with no loss of accuracy or efficiency, and are fabricated from optoelectronically-active elements to minimize static charging during repeated use.

Abstract: A novel, advanced polymeric swab is disclosed herein. The swabs have a surface texture that allows for independent motion between microscale regions, are reusable with no loss of accuracy or efficiency, and are fabricated from optoelectronically-active elements to minimize static charging during repeated use.