Binary Communication Network Matrices for Human–Algorithmic Interaction in Three Product IT Organizations

This dataset contains binary communication network data from three product IT companies. The data were collected through an online survey completed by 145 employees: 42 from Company A, 49 from Company B, and 54 from Company C. The dataset includes one adjacency matrix for each company. Each matrix captures reported work-related communication as a directed network. In addition to the employee nodes, every network includes an AI node representing employees’ use of artificial intelligence as a source of work-related information and support. The AI node is an analytical element of the network and does not represent an additional survey participant. The resulting matrix dimensions are 43 × 43 for Company A, 50 × 50 for Company B, and 55 × 55 for Company C. A value of 1 indicates that a directed communication tie is present, while a value of 0 indicates that no such tie was reported. The matrices can be used to analyse network density, geodesic distance, degree centrality, closeness centrality, betweenness centrality, the concentration of communication activity, network fragmentation, and the position of AI within organizational information flows. To protect confidentiality, the names of the companies and the identities of individual participants have not been disclosed. The companies are labelled A, B, and C, and the files contain no names or other direct personal identifiers. The matrices are provided as Microsoft Excel files and can be analysed in UCINET or other software that supports binary adjacency matrices.