The invention discloses a method for automatically constructing a strategic emerging industrial chain based on patent information, belongs to the technical field of strategic emerging industrial chain construction, and aims to solve the problems of one-sided data coverage, low construction precision and lack of dynamic early warning of an existing method. The method comprises the following five core steps: S1, data batch division: dividing patent technology and industry associated target data into batches 1, 2,..., n (n is preferentially 20) according to quarterly; s2, multi-dimensional data collection: synchronously collecting patent technology data such as patent nodes, patent quotation, patent-industry relationships and the like, and industry associated data such as industry technologies, upstream supply and demand, downstream markets and the like; s3,
data processing: calculating a patent node dominance degree coefficient, a patent
citation value coefficient, an industry integrating degree coefficient, an industry technology association fusion degree coefficient, an industry upstream association dependency coefficient and an industry downstream relationship development potential coefficient through the exclusive model; s4, comprehensive evaluation: calculating a comprehensive evaluation index R through min-max normalization and an
entropy weight method (
weight distribution: alpha i0.2,
lambda i0.2,
delta i0.15, beta'i0.15, gamma'i0.15 and epsilon'i0.15); and S5, performing final judgment, and sending out a normal / early warning
signal based on the R preset value 0.65 (30 qualified industrial chain
statistical mean). Through deep fusion, quantitative modeling and dynamic evaluation of patent and industry data, the industrial
chain structure matching degree reaches 92.3%, the core node identification accuracy reaches 89.7%, only 2.5 hours are needed for
processing 100,000 pieces of patent data, risks such as upstream
raw material shortage and downstream demand insufficiency can be positioned in time, and the method is suitable for large-scale popularization and application. The method is suitable for strategic emerging industries such as
new energy, semiconductors and biological
medicine, and provides support for industry chain optimization and
decision making.