| WHO英文网站健康主题语义链接关系社会网络分析 |
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| 引用本文： | 刘红霞,张进,陈璟浩.WHO英文网站健康主题语义链接关系社会网络分析[J].图书情报工作,2014,58(13):75-82. |
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| 作者姓名： | 刘红霞 张进 陈璟浩 |
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| 作者单位： | 1. 中国人民大学信息资源管理学院;
2. 威斯康辛大学密尔沃基分校(UWM)信息学院;
3. 武汉大学信息管理学院 |
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| 基金项目： | 本文得到国家留学基金委资助。 |
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| 摘 要： | 选择世界卫生组织（WHO）网站健康信息主题作为研究对象，统计各个健康主题的互链数据，利用文本相似性算法并基于语义的角度，运用社会网络分析方法和Ucinet软件，从中心度、密度、凝聚子群角度分析这些健康主题之间的社会网络关系，最终证实挖掘的健康主题信息与2013年世界卫生报告中阐述的全民健康覆盖目标信息相匹配。
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| 关 键 词： | 健康主题 WHO 中心度 密度 凝聚子群 |
| 收稿时间： | 2014-04-18 |
| 修稿时间： | 2014-06-09 |
Social Network Analysis of Semantic Links Relationships Among Health Topics in WHO English Website |
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| Liu Hongxia,Zhang Jin,Chen Jinghao.Social Network Analysis of Semantic Links Relationships Among Health Topics in WHO English Website[J].Library and Information Service,2014,58(13):75-82. |
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| Authors: | Liu Hongxia Zhang Jin Chen Jinghao |
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| Institution: | 1. School of Information Management, Resource Renmin University of China, Beijing 100872;
2. School of Information Studies University of Wisconsin-Milwaukee, Milwaukee 53211;
3. School of Information Management, Wuhan University, Wuhan 430072 |
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| Abstract: | With healthcare being a hot topic and the development of the Webometrics, link analysis is becoming a hot topic. Taking the World Health Organization (WHO) English website as the object of research, this paper makes a statistics of mutual chain data of health topics. With text similarity algorithm and based on semantic links, using social network analysis methods and Ucinet software, it analyzes the social network relationships among these topics from the perspectives of the centrality, density and cohesion subgroup. Finally, it verifyies that the information excavated from health topics matches to that of the universal health coverage targets in 2013 World Health report. |
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| Keywords: | subject topics World Health Organization (WHO) centrality density cohesion subgroup |
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