信息资源管理学报 ›› 2021, Vol. 11 ›› Issue (1): 90-97.doi: 10.13365/j.jirm.2021.01.090

• 研究论文 • 上一篇    下一篇

在线医患沟通中的知识不对称研究

陆泉1,3 李畅1 刘婷1 陈静2   

  1. 1. 武汉大学信息资源研究中心,武汉,430072;
    2.华中师范大学信息管理学院,武汉,430079;
    3.武汉大学大数据研究院,武汉,430072
  • 出版日期:2021-01-26 发布日期:2021-02-02
  • 作者简介:陆泉,教授,博士生导师,研究方向为数据挖掘、知识组织与服务;李畅,硕士生,研究方向为健康信息研究,知识服务;刘婷,博士生,研究方向为用户行为,知识服务;陈静(通讯作者),教授,Email:dancinglulu@sina.com,研究方向为知识服务,数据挖掘,用户研究。
  • 基金资助:
    国家社会科学基金重点项目“心理账户理论视角下在线健康社区精准信息服务研究”(20ATQ008)和教育部人文社会科学重点研究基地重大项目“大数据资源的挖掘与服务研究——面向医疗健康领域”(17JJD870002)。

Research on the Knowledge Asymmetry in Online Doctor-Patient Communication

Lu Quan1,3 Li Chang1 Liu Ting1 Chen Jing2   

  1. 1.Center for the Studies of Information Resources, Wuhan University, Wuhan 430072; 
    2. School of Information Management, Central China Normal University, Wuhan 430072; 
    3. Big Data Research Institute, Wuhan University, Wuhan 430072
  • Online:2021-01-26 Published:2021-02-02

摘要: 在线医患沟通是网络医疗健康服务的主要形式,深度分析其中的医患知识不对称规律有助于消除医患沟通障碍。本研究选取“春雨医生”在线沟通数据,从关键词主题、概念和语义关系三个维度探索知识不对称规律。结果表明:①医患关键词主题存在阶段差异,患者多关注“症状描述”“询问治疗”等主题,集中于主诉和治疗阶段,医生多关注“疾病解释”“治疗建议”等主题,集中于诊断和治疗建议阶段;②在概念理解上,医生的用词专业性更高,知识表达更准确;③医生的关键词间语义依存关系种类更多,关联强度更大。研究结果有助于提高医患沟通效率,促进在线医患沟通服务的发展。

关键词: 在线医患沟通, 知识不对称, 概念表达, 语义依存关系, 文本挖掘, 语义分析

Abstract: Online doctor-patient communication is the main form of online health services. The deep analysis of the knowledge asymmetry can help eliminate doctor-patient communication barriers. This article selects the online dialogue data from "Dr. Chunyu", and explores the rule of knowledge asymmetry from three dimensions: keyword topics, concept and semantic relationship. The results show that patients pay more attention to topics such as "symptom description" and "inquiry treatment", focusing on complaint and treatment stages,while doctors pay more attention to topics such as "disease explanation", and "treatment recommendation", focusing on diagnosis and treatment recommendation stages. In terms of concept understanding, doctors use more professional words and express knowledge more accurately. Doctors have more types of semantic dependencies between keywords, and stronger association strength. The research results can improve the efficiency of doctor-patient communication and promote the development of online doctor-patient communication services.

Key words: Online doctor-patient communication, Knowledge asymmetry, Concept expression, Semantic dependency, Text mining, Semantic analysis

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