Paper Title
An Exploratory Study on Water Management with LDA Topic Modeling

In recent years, the water management (WM) research area has gained remarkable attention, especially in the sustainability research area, because globally, we face water scarcity, which could be a considerable challenge in the coming years. WM term has been argued in several research areas. However, there is no definition of WM and it is not clear that WM is appliedin which research context in the scientific area. This study aims to identify topics within WM to find research areas in WM and propose a better academic definition of WM. In this study, 1,324 articles from the Web of Science database were selected, and a text mining approach,Latent Dirichlet Allocation (LDA), wasapplied to identify topics within WM. The result demonstrated the following five topics that have been arguedin academia: (1) water management in membrane fuel cells, (2) agriculture, (3) wastewater management (treatment or reuse), (4) Sustainable urban water management, and (5) river and groundwater management. Keywords - Water Management, Text Mining, LDA, Topic Modelling, Latent Dirichlet Allocation