Quantitative Evaluation of Pharmaceutical Industry in Jilin Province Based on Text Mining

Abstract

The pharmaceutical industry has evolved into one of the most strategically focused developing sectors as a result of the high prevalence of several epidemic viruses in recent years. Analysis of the effectiveness of Jilin Province's pertinent pharmaceutical policies is necessary since the province is a significant source of medicinal resources in China with a wealth of herbal medicine reserves as well as clear advantages in the growth of the pharmaceutical industry. The text mining methods employed in this paper include LDA topic modelling, word frequency analysis, and keyword extraction. To visually analyze the policy themes and priorities of China's pharmaceutical industry during the past ten years, 33 important pharmaceutical industry policies that were made public at the national level in that country between 2012 to 2022 are utilized as text mining objects. Along with pertinent references, the text mining results are used as a blueprint to create a more rigorous pharmaceutical industry assessment index system. Finally, we adopt the PMC model to quantitatively evaluate the key pharmaceutical policies issued by the Jilin government in recent years, analyzed the heterogeneity, strengths, and weaknesses of each key pharmaceutical policy in Jilin Province from a variety of dimensions and put forward reasonable suggestions for the improvement of relevant policies.