摘要
研究旨在通过分析湖南省政府数据开放平台的用户反馈评论数据,识别公众在教育、职业资格认证、农村发展、养老保险、基础设施建设等领域的关注点与需求,并提出相应的政策改进建议。采用文本挖掘技术,使用Python对评论数据进行采集和预处理,并通过BERTopic模型提取主题,揭示公众主要关注的领域。研究结果显示,公众在教育、农村发展、医疗、退役军人就业等方面有较高关注。基于此,提出了提升就业服务、加强政府沟通、完善养老保险制度、提供退役军人就业支持四项改进建议,以提高政府公共服务质量。
By analyzing the user feedback comment data from the Hunan provincial government open data platform,this research aims to identify the public's concerns and needs in education,professional qualification certification,rural development,pension insurance,infrastructure construction and other fields,and propose corresponding policy improvement suggestions.It uses text mining techniques,employs Python to collect and preprocess the comment data,and extracts topics through the BERTopic model,revealing the main fields of public concern.The research results indicate that the public shows significant attention to education,rural development,healthcare,and employment for veterans.Based on these findings,four recommendations for improvement are proposed,including enhancing employment services,improving government communication,refining the pension insurance system,and providing employment support for veterans,so as to improve the quality of government public services.
作者
郑昂
彭纪扬
ZHENG Ang;PENG Jiyang(Tourism College of Jishou University,Zhangjiajie 427000,China)
出处
《现代信息科技》
2025年第4期87-92,共6页
Modern Information Technology
基金
吉首大学研究生校级科研项目(Jdy23214)。
