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.