摘要：

Abstract:

【Purpose/significance】 Against the backdrop of the global emerging technology revolution and industrial transformation,

this study focuses on the new energy vehicle industry. It employs a multi-dimensional perspective to analyze open-source technologi⁃

cal intelligence, aiming to reveal the industry's key technologies and development trends.【Method/process】 The research collected

patent data, social media texts, and policy documents. It utilized patent data to construct citation networks and identify primary path⁃

ways, systematically analyzing the key technologies and development trajectory of the new energy vehicle industry in conjunction with

lifecycle theory. The study trained social text classification models using Support Vector Machine classifiers and employed time-series

analysis to observe the trends in industry topics that users focus on, exploring public attitudes and opinions towards new energy ve⁃

hicles. It also used LDA to conduct phased topic extraction from policy texts, revealing the impact of policies on industry development.

【Result/conclusion】 Through multi-dimensional comparative analysis, the study categorized the impacts of interactions among enter⁃

prises, government, and users in the development of the new energy vehicle industry into four types: expansion of market size, iterative

technological upgrades, infrastructure construction, and industry regulation norms. This provides references and insights for the devel⁃

opment path of the industry following the reduction of new energy vehicle subsidies.【Innovation/limitation】 The research was not com⁃

prehensive enough in the selection of data sources, lacking in depth and breadth.