摘要
Abstract
According to users’ comments and feedback on the open platform of government data, this paper makes sentiment analysis through subject classification, clarifies users’ satisfaction with the service provided by the platform and the existing problems, and provides new analysis ideas for optimizing the construction of open data platform. Firstly, the LDA model is used to extract the topic from the user comment data of Wuhan Government Open Data Website, and the deep neural network is used to classify the comment. On this basis, sentiment analysis is carried out to explore the emotional differences of different types of comment. LDA model extracts nine categories of topics. Combining with the results of emotional analysis, the emotional trend of two topics is satisfactory, and the emotional trend of six topics is general or unsatisfactory. Based on the analysis results, the deficiencies in platform services are summarized and the corresponding optimization strategies are put forward.关键词
主题模型/政府数据开放平台/情感分析/情感差异Key words
Topic Model/Government Data Open Platform/Sentiment Analysis/Sentiment Diversity分类
社会科学
