A scientometric review of blockchain research

As a new and rapidly developing distributed technology, blockchain has shown substantial impact on the fields of cryptocurrency and e-commerce and thus has attracted the interests of governments, enterprises, and research institutions. As such, it is important to understand the state of blockchain research in order for those institutions to plan their research effectively. Towards this goal, we first integrate two search strategies to construct a representative dataset. Then we analyze the blockchain literature between 2013 and 2018 in this dataset with a science mapping approach and Latent Dirichlet Allocation model. Based on the results of the analysis, we found the following insights: (1) the evolution of blockchain research involves many disciplines while two major disciplines—computer science and business—lead the way. (2) The current research can be divided into four research areas: underlying technology architecture, privacy and security, financial application, and smart scene applications. (3) The evolution of blockchain research has gone through three stages: basic blockchain technology, various business applications, and integration with advanced technologies such as fog computing, Internet of things, and artificial intelligence. (4) We also discovered a close coupling of two research issues that have transformative power, i.e., the potential by the application of cryptocurrency in the real world and the improvement of blockchain technology based on the application requirements. Overall, our study uses multiple complementary scientometric methods to generate a panoramic view of the recent developments in blockchain research. Future research directions and some limitations are discussed.