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. 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.
|Journal||Transactions of the Japanese Society for Artificial Intelligence|
|Publication status||Published - 2022|
- Business chat data
- Multivariate Hawkes process
- Network analysis
ASJC Scopus subject areas
- Artificial Intelligence