Analyzing public demands on China's online government inquiry platform: A BERTopic-Based topic modeling study.

ABSTRACT: This study aims to enhance governmental decision-making by leveraging advanced topic modeling algorithms to analyze public letters on the "People Call Me" online government inquiry platform in Zhejiang Province, China. Employing advanced web scraping techniques, we collected publicly available letter data from Hangzhou City between June 2022 and May 2023. Initial descriptive statistical analyses and text mining were conducted, followed by topic modeling using the BERTopic algorithm. Our findings indicate that public demands are chiefly focused on livelihood security and rights protection, and these demands exhibit a diversity of characteristics. Furthermore, the public's response to significant emergency events demonstrates both sensitivity and deep concern, underlining its pivotal role in

SUBMITTER: Tang Z 

PROVIDER: S-EPMC10868819 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature