[1I4-GS-2] Machine learning: Applied machine learning (1)

[1I4-GS-2-04] Network Analysis between Employees based on Business Chat Data

〇Kenya Nonaka¹, Haruka Yamashita², Masayuki Goto¹ (1. Waseda University, 2. Sophia University)

Keywords:network analysis, bussiness chat data, multivariate hawkes process

Visualizing social relationships by a network is useful for understanding the behavior of groups and individuals. The target of this study is a network between employees in the workplace. The construction of this network enables us to understand human relationships and managing a team. To build this network, the questionnaire and e-mail data were conventionally used. However, in this work, we use conversation history data on a chat application(Slack, etc.). We propose a method of quantifying the relationship between employees from conversation data on a chat application and visualizing it as a network between employees. Specifically, we assume that strongly related employees will make remarks at adjacent times on the chat, quantify the relationship by multivariate hawkes process and build a network model. To verify the effectiveness of the proposed model, we used Slack conversation data of a real company and extracted knowledge about team management from the network.