Identification of Emerging Technological Hotspots from a Multi-Source Information Perspective: Case Study on Blockchain Financial Technology

In recent years, propelled by societal transformations and technological advancements, emerging technologies founded upon diverse disciplines such as financial and information technology have rapidly evolved. Identifying the trends associated with these emerging technologies and extracting their salient topics is crucial in order to accurately grasp the developmental trajectory of these tools and for their efficient utilization. In this study, we chronologically categorize information derived from five types of multi-source data, including journal articles, patent inventions, and industry reports, into distinct periods. We employ the LDA (Latent Dirichlet Allocation) topic model to identify emerging technological themes within these periods and utilize a dual-index theme lifecycle analysis method to construct a hotspot theme distribution map, thereby facilitating the extraction of significant themes. Through empirical research on blockchain financial technology, we ultimately identify 22 thematic areas of blockchain finance and extracted eight prominent themes, including financial technology, cross-border payments, digital invoices, supply chain finance, and decentralization. By analyzing these themes alongside their respective popularity levels, we validate that the methods above can be used to effectively identify emerging technological hotspots and illuminate their developmental directions.