【摘要】 目的/意义借助文本内容分析法对互联网医疗平台用户发布的信息质量进行评价研究。方法/过程通过Python爬虫获取国内典型互联网医疗平台的文本内容，进行自然语言处理和聚类分析，提取特征指标设计逻辑回归模型并进行灰色关联度修正，从而构建信息质量评价指标体系。结果/结论互联网医疗平台可重点从信息丰富度、信息发布者特征及用户交流互动方面加强信息的发布与呈现，引导用户发布高质量信息并快速识别有价值信息，促进互联网医疗平台的可持续发展。更多还原

【Abstract】 Purpose/Significance To evaluate and study the quality of information published by users of internet medical platforms using text content analysis method. Method/Process The text content of typical internet medical platforms in China is obtained by Python crawler, natural language processing(NLP) and clustering analysis are performed. Feature indexes are extracted and logistic regression model and grey relational degree correction are designed to construct an information quality evaluation index system. Result/Conclusion The information release and presentation of internet medical platforms can be strengthened from the aspects of information richness, characteristics of information publishers and user interaction, and users can be guided to release high-quality information and quickly identify valuable information, so as to promote the sustainable development of internet medical platforms.更多还原