Presenting contents of unstructured data (documents) in the form of a as semantic network in manual, semi-manual, and automated means•
Showcased the use of network analysis to capture and analyze knowledge contained in unstructured data•
Used blockmodeling technique to cluster network and discover possible knowledge constructs•
Evaluated the proposed approach through three case projects, a questionnaire and a focus group
Unstructured data, mainly text in project documents and final evaluation or summary reports, is a container of tacit knowledge. We present an exploratory case study to use semantic network analysis to help capture and formalize elements of this knowledge. Text from project documents and chats by project participants over an interactive BIM platform were collected and arranged in the form of concept networks. With that, we used the rich literature in network science to formally study the networks. We illustrate the proposed approach by analyzing five concept networks. The case study illustrates the benefits of the approach—mainly, to develop a project-specific map of key concepts. Using network measures, such as centrality, identified the project’s key issues and how they relate. Clustering measures identified possible knowledge constructs (interrelated concepts). Measures for quantifying the overall structure of the network can also be used to contrast projects.