基于文本内容分析的互联网医疗平台信息质量评价研究  

Study on Information Quality Evaluation of Internet Medical Platforms Based on Text Content Analysis

作　　者：王君[1] 姚唐[1] 王亚妮 WANG Jun;YAO Tang;WANG Yani(School of Economics and Management,Beihang University,Beijing 100191,China;Yanjing Medical College,Capital Medical University,Beijing 101300,China)

机构地区：[1]北京航空航天大学经济管理学院,北京100191 [2]首都医科大学燕京医学院,北京101300

出　　处：《医学信息学杂志》2023年第11期7-12,29,共7页Journal of Medical Informatics

基　　金：首都医科大学校自然培育项目(项目编号:PYZ22037);北京市教委社科一般项目(项目编号:SM202310025001)。

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。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.

关 键 词：互联网医疗 信息质量评价 文本内容分析 逻辑回归 灰色关联度修正 

分 类 号：R-058[医药卫生]