{"title":"艾滋病研究中临床和学术领域合作网络的探索:一种空间科学计量方法","authors":"Y. Jeong, Dahee Lee, Min Song","doi":"10.1145/2665970.2665982","DOIUrl":null,"url":null,"abstract":"This study investigates the world-wide collaborative networks from a geographical perspective based on clinical tests (CT) and academic researches (AR) on Acquired immune deficiency syndrome or acquired immunodeficiency syndrome (AIDS). By applying text mining technique on the AIDS related documents, we extract the spatial information and are able to discover co-location pairs for each type of research at two levels: national level and city level. Co-location networks for CT and AR are analyzed using network features, visualization, and highly-ranked betweenness centrality nodes. The analysis results reveal that the CT network is more densely compact with about twice as many nodes than the AR network. According to the analysis at the national level, the AR network is rather focused on the United States while the CT network is more spread out throughout the world. At the city level, the collaborative work is more active among closely located cities in the AR network compared to the case of the CT network (see Figure 1). The AR network has core collaboration centers mainly situated in the United States and Europe, but those of the CT network also includes Asian and African cities. Overall, our study intuitively points out the differences in the collaborative networks for CT and AR, which contributes to the understanding of the research trend involving the productivity analysis of the collaborative work associated with the regional aspect.","PeriodicalId":143937,"journal":{"name":"Data and Text Mining in Bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Exploration of the Collaborative Networks for Clinical and Academic Domains in AIDS Research: A Spatial Scientometric Approach\",\"authors\":\"Y. Jeong, Dahee Lee, Min Song\",\"doi\":\"10.1145/2665970.2665982\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study investigates the world-wide collaborative networks from a geographical perspective based on clinical tests (CT) and academic researches (AR) on Acquired immune deficiency syndrome or acquired immunodeficiency syndrome (AIDS). By applying text mining technique on the AIDS related documents, we extract the spatial information and are able to discover co-location pairs for each type of research at two levels: national level and city level. Co-location networks for CT and AR are analyzed using network features, visualization, and highly-ranked betweenness centrality nodes. The analysis results reveal that the CT network is more densely compact with about twice as many nodes than the AR network. According to the analysis at the national level, the AR network is rather focused on the United States while the CT network is more spread out throughout the world. At the city level, the collaborative work is more active among closely located cities in the AR network compared to the case of the CT network (see Figure 1). The AR network has core collaboration centers mainly situated in the United States and Europe, but those of the CT network also includes Asian and African cities. Overall, our study intuitively points out the differences in the collaborative networks for CT and AR, which contributes to the understanding of the research trend involving the productivity analysis of the collaborative work associated with the regional aspect.\",\"PeriodicalId\":143937,\"journal\":{\"name\":\"Data and Text Mining in Bioinformatics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Data and Text Mining in Bioinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2665970.2665982\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Data and Text Mining in Bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2665970.2665982","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Exploration of the Collaborative Networks for Clinical and Academic Domains in AIDS Research: A Spatial Scientometric Approach
This study investigates the world-wide collaborative networks from a geographical perspective based on clinical tests (CT) and academic researches (AR) on Acquired immune deficiency syndrome or acquired immunodeficiency syndrome (AIDS). By applying text mining technique on the AIDS related documents, we extract the spatial information and are able to discover co-location pairs for each type of research at two levels: national level and city level. Co-location networks for CT and AR are analyzed using network features, visualization, and highly-ranked betweenness centrality nodes. The analysis results reveal that the CT network is more densely compact with about twice as many nodes than the AR network. According to the analysis at the national level, the AR network is rather focused on the United States while the CT network is more spread out throughout the world. At the city level, the collaborative work is more active among closely located cities in the AR network compared to the case of the CT network (see Figure 1). The AR network has core collaboration centers mainly situated in the United States and Europe, but those of the CT network also includes Asian and African cities. Overall, our study intuitively points out the differences in the collaborative networks for CT and AR, which contributes to the understanding of the research trend involving the productivity analysis of the collaborative work associated with the regional aspect.