A Method for Network Construction Based on Communication Data on Business Chat Application

Kenya Nonaka, Haruka Yamashita, Hajime Hotta, M. Goto
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Abstract

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.
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一种基于通信数据的商务聊天应用网络构建方法
通过网络可视化社会关系对于理解群体和个人的行为是有用的。本研究的目标是员工在工作场所之间的网络。这个网络的构建使我们能够理解人际关系和管理一个团队。为了建立这个网络,通常使用问卷调查和电子邮件数据。然而,在这项工作中,我们使用了聊天应用程序(Slack等)上的会话历史数据。我们提出了一种方法,通过聊天应用程序上的对话数据来量化员工之间的关系,并将其可视化为员工之间的网络。具体来说,我们假设强关联员工会在聊天中相邻的时间发表评论,并通过多元Hawkes过程量化这种关系,构建网络。为了验证所提出模型的有效性,我们使用了一家真实公司的Slack会话数据,并从网络中提取了关于团队管理的知识。
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Transactions of The Japanese Society for Artificial Intelligence
Transactions of The Japanese Society for Artificial Intelligence Computer Science-Artificial Intelligence
CiteScore
0.40
自引率
0.00%
发文量
36
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