A Speech Data-Driven Stakeholder Analysis Methodology Based on the Stakeholder Graph Models

摘要

Among the requirements elicitation activities, the stakeholder analysis is the main source of requirements. In this article, we propose a new model of data-driven stakeholder analysis, named SIG (Stakeholder Intention Graph), a semantic extension of property graph model that can represent the stakeholders' intentions and their relationships. To elicit the stakeholders' intentions from the speech data during meetings, we developed a system of structural analysis and SIG generation method from speech data. Based on the graph theory, we also propose an analysis methodology of stakeholders' intentions and their structure with both global and local graph analyses. We implemented a speech data-driven stakeholder analysis system on the graph database Neo4j. As the output, the analysis system automatically generates the stakeholder matrix from the speech data at the meetings. We applied the analysis method and system to the speech data of actual development meetings on the public service systems, and demonstrated the effectiveness of the proposed method.