Conditional Visualization Analysis Model for Communication between Employees on Business Chat App

Abstract

If network visualization can be achieved from the conversation data accumulated on business chat apps, which has recently been utilized, the actual state of communication within workplace teams for business purposes can be clarified, and it has the potential to be useful for various measures and decision making. In the network analysis that visualizes communication among employees, each employee is represented by a node and the communication statuses are represented by links between nodes. Although the employees represented by each node can be uniquely defined for a target company, the relationship between nodes can be variously defined from the different viewpoints and analysis purposes. That is, the meaning of the links changes depending on the conversation conditions (communication conditions) used to define edges, such as the content of statements, topics, and groups to which the employees belong. It would be beneficial from the viewpoint of organizational management if a method for analyzing differences and similarities in network structures due to such differences in conditions was provided. This study proposes a network analysis method for communication data on business chat apps, which quantitatively analyzes and visualizes changes in employee network structure due to differences in communication conditions. The proposed method makes it possible to visualize changes in network structure associated with different communication conditions and communication conditions with structures that differ significantly from the overall communication structure in a form that is easy to interpret and can be used for various measures and decision making. This study demonstrates the effectiveness of this method for analyzing relationships among employees by using actual conversation history data.