The Regional Clusting Effect of the Blockchain Industry Base on Unsupervised Learning Methods

Yuxi Zhang, Muran Su, Zhen Wu, Xiang Chen, Haifeng Guo, Xinxin Chang, Hongzhi Wang

Abstract: The blockchain industry has developed rapidly in China last years, but in an extremely uneven pattern, especially in different regions. This paper adopts unsupervised learning methods to delineate the uneven regional patterns in the blockchain industry. We conduct the analysis in five aspects, including blockchain company, blockchain projects, R&D ability, financing and talents allocation. We find that the blockchain industries cluster in four area, i.e., Guangdong, Beijing, Jiangsu, Zhejiang etc. However, since most of China’s R&D activities are based on universities and research institutes, which tend to be concentrated in cities, the cluster of R&D capabilities is city-centric, other than area. Financing and talents allocations show similar clustering effect in different regions.