Study on data mining of hydrogen energy policy in China based on natural language processing technology postprint

Abstract: Report to the 20th National Congress of the CPC emphasized the importance of “working actively and prudently towards the goals of reaching peak carbon emissions and carbon neutrality”, as well as “speeding up the planning and development of a system for new energy sources”. As a green and low-carbon secondary energy source, hydrogen energy has multiple applications in promoting the large-scale and efficient use of renewable energy as well as energy substitution in the field of transportation. It can also accelerate decarbonization in industry, and as such, is an indispensable part of building a new energy system, reaching peak carbon emissions and achieving carbon neutrality. This study takes 621 hydrogen energy policy documents issued by national and local government as research objects, designating to comprehensively study the hydrogen energy policy system. Based on policy informatics, this study uses natural language processing technology to mine data deeply and draws on hydrogen energy policy element information and key data indicators. It also combines content analysis, quantitative analysis and makes use of data visualization technology to study the evolution of hydrogen energy policy. It examines evolution trajectory of hydrogen energy policy, regional patterns of industry, the industrial chain layout, and other characteristics. The research framework and analysis methods used herein can help improve the systematization and timeliness of hydrogen energy policy research and proposes hydrogen energy policy suggestions to accelerate the development of hydrogen energy.