AN INTEGRATED SCIENTOMETRIC AND SNA APPROACH TO EXPLORE THE CLASSICS IN CEM RESEARCH

Abstract

This study explores the classics that significantly contribute to the research of construction engineering and management (CEM). Previous studies usually simply applied the number of citation to identify the classics, causing some flaws. To overcome the flaws, an advanced approach is developed by integrating scientometric methods (G-index and co-citation analysis) and a social network analysis (SNA) technique (modularity optimization algorithm), thus providing more precise and persuasive results that denote what academic works have made significant inspirations and illuminations on CEM research. This study retrieves 13,273 CEM literature and extracts 336,129 bibliographies from these literature. Based on the G-index, a total of 67 publications are identified as CEM classics. Moreover, this paper measures and maps the structure of the classics by using co-citation analysis and modularity optimization algorithm. The results provide a basic source of academic information representing the foundation of CEM and draw a big picture of CEM to show the underlying associations between the identified classics. This can help researchers recognize the key scientific contributions for improving the academy progress.