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基于社会网络分析的公众健康网群影响力研究
引用本文:门伟莉,杜建,唐小利.基于社会网络分析的公众健康网群影响力研究[J].医学信息学杂志,2016,37(5):2-9.
作者姓名:门伟莉  杜建  唐小利
作者单位:中国医学科学院医学信息研究所 北京 100005;中国医学科学院医学信息研究所 北京 100005;中国医学科学院医学信息研究所 北京 100005
基金项目:十二五国家科技支撑计划(项目编号:2013BAI06B00)。
摘    要:运用社会网络分析法,从健康类网站AlexaTop200和2015年复旦大学医院评价综合榜及医学领域学协会网站中筛选182个有效网站,根据主办单位性质划分为企业、个人、专业机构、社会团体和政府5个子群。基于网站间的链接关系构建整体网和子群的网络关系图,对比分析整体网群和子群的网络结构、中心度和网络的关联性,发现不同类型网站在规模和结构上的异同及各网群影响力差异,为完善大众健康类网群的建设、改善健康信息服务现状提供借鉴。

关 键 词:社会网络分析  网络结构  中心度  关联度  网群影响力
收稿时间:2016/1/18 0:00:00

Research on the Influence of Public Health Nets Based on Social Network Analysis
MEN Wei-li,DU Jian and TANG Xiao-li.Research on the Influence of Public Health Nets Based on Social Network Analysis[J].Journal of Medical Informatics,2016,37(5):2-9.
Authors:MEN Wei-li  DU Jian and TANG Xiao-li
Institution:Institute of Medical Information, Chinese Academy of Medical Science, Beijing 100005, China;Institute of Medical Information, Chinese Academy of Medical Science, Beijing 100005, China;Institute of Medical Information, Chinese Academy of Medical Science, Beijing 100005, China
Abstract:By using the method of social network analysis, the paper screens 182 valid nets out of health in AlexaTop200, 2015 Comprehensive Hospital Evaluation List by Fudan University and nets of associations in the medical field, and divides them into 5 subgroups by the nature of nets sponsors, namely enterprises, individuals, professional institutions, social organizations and governments. Based on the link relations among these nets, it builds the diagram of network relationship between the whole nets and the subgroups, compares and analyzes the network structure, centrality and network relevance of the whole nets and the subgroups, and finds out the similarities and differences of different types of nets in the size and structure and the influence differences of different nets. It provides reference for the development of public health nets and the improvement of current health information services.
Keywords:Social network analysis  Network constructs  Centrality  Connectedness  Nets influence
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