Text analytics to analyze and monitor construction project contract and correspondence

Text mining is a fast-growing area of research, due to its ability to discover valuable information and getting insights hidden in plain texts. The aim of this paper is to apply text mining in order to analyze construction project contracts and visually analyze project correspondence. Analyzing construction contract helps project parties to figure out their obligations and reduce time and effort needed for contract analysis. Additionally, performing text mining to the contract helps in extracting critical keywords that should be monitored closely in the correspondence. On the other hand, applying text mining for project correspondence helps in gaining an understanding regarding the communication nature and sentiment between project parties. Thus, the paper develops a Dynamic Text Analytical model for Contract and Correspondence DTA-CC through utilizing BIM. The DTA-CC model assists project parties to explore texts and get insights regarding the project performance. The specific objectives of this study are to 1-perform a text analytics of the construction project contract, 2-integrate project correspondence within the BIM model and 3- develop a text analytical model based on project's correspondence to monitor the project performance. The DTA-CC model is validated by applying a case study for a construction project located in Cairo, Egypt. The case study found that there is a lot of hidden information in the project's raw data. Moreover, it is crucial to monitor raw data in order to achieve a successful project. This study extends the existing knowledge by proposing a novel methodology to extract meaningful patterns from construction projects data.