Patterns and trends in Building Information Modeling (BIM) research: A Latent Semantic Analysis

• This study systematically analyses a large corpus of BIM literature including 975 papers.
• Latent Semantic Analysis (LSA) was applied to identify the core and detailed patterns and trends in BIM research.
• Semantic links between core and detailed research patterns were established systematically.

Building Information Modeling (BIM) has emerged as one of the key streams in construction and civil engineering research within the last decade. Given this interest in BIM and the rapidly increasing volume of BIM literature, it is important to understand and discern the core themes and trends emerging in BIM research, and its implications for broader research. The previously reported studies to identify the core of BIM research are typically subjective and qualitative, and hence, prone to bias and interpretation of a limited number of reviewed papers. There is a lack of comprehensive, quantified and systematic classification of the BIM literature. This research brings some clarity by synthesizing and labeling a large corpus of BIM research studies published from 2004 through 2014. Latent Semantic Analysis (LSA), a natural language processing technique was applied to the abstracts of 975 academic papers. This objective analysis reveals twelve principal research areas. Various specific research themes associated with each principal area have been identified. These principal research areas and research themes indicate the patterns and trends in BIM research.