Peoplet: Exploring Organizational Structures Through Social Network Analysis

In this paper, we propose an approach based on multilayer networks to represent various aspects of relationships within an organizational structure. The model captures multiple layers of organizational interactions, including hierarchical relationships, connections based on shared expertise and common interests, and affiliations with the same organizational unit. A distinctive feature of the proposed approach is the integration of survey data to construct specific network layers, enabling a more detailed representation of interpersonal and intergroup links. To extract relevant relationships from survey responses, we employ prompt engineering, ensuring an efficient and structured transformation of textual data into network elements. To account for the complexity of relationships within an organization, we propose a multilayer network representation that enables a comprehensive analysis of complex structures within organisation. The proposed approach is implemented within the Peoplet application and validated through a case study exploring a multilayer network constructed from the University of Rijeka, Faculty of Informatics and Digital Technologies (FIDIT) data. Our findings confirm that the proposed approach provides a deeper understanding of organizational structures, offering valuable insights for optimizing collaboration, communication, and decision-making within organizations.