Social Network Analysis of Semantic Links Relationships Among Health Topics in WHO English Website

  • Liu Hongxia ,
  • Zhang Jin ,
  • Chen Jinghao
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  • 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

Received date: 2014-04-18

  Revised date: 2014-06-09

  Online published: 2014-07-05

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.

Cite this article

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 . DOI: 10.13266/j.issn.0252-3116.2014.13.013

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Outlines

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