语义网络链接分析,发现学术团体中的社会关系

T. Miki, Saeko Nomura, T. Ishida
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引用次数: 28

摘要

为了发现研究人员网站之间的链接如何准确地捕捉到学术团体之间的联系,本研究进行了网络引文分析。评估了3878个计算机科学家的网站和8811篇论文。其中200名最常被引用的研究人员进行了网络作者分析,并与书目数据进行了比较。因此,网络上的研究人员集群成为书目集群的超集,即一个代表更大研究领域的社区。然后,我们开发了定义研究人员之间各种关系的Web链接本体,以便对200个站点之间的链接应用元数据注释。研究结果如下:1)由于智力联系分析分离了社会认知联系,它可以更好地近似于书目作者交流;2)由于社会认知联系分析可以利用各种联系,不仅是共同作者网络,还可以找到各种各样的社会联系;3)将智力联系和社会认知联系分析结合起来,可以发现在社会网络上连接研究领域的看门人。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Semantic Web link analysis to discover social relationships in academic communities
To discover how precisely links among researchers' Web sites capture the ties of academic communities, this study conducts Web citation analysis. 3,878 Web sites of computer scientists and their 8,811 articles are assessed. 200 most frequently cited researchers from them are subjected to Web author cocitation analysis and compared to bibliographical data. As a result, a cluster of researchers on the Web becomes a superset of bibliographical one, that is, a community representing a larger research field. We then develop Web link ontology that defines various relationships among researchers to apply metadata annotation to the links among 200 sites. The findings are 1) since intellectual ties analysis separates off sociocognitive ties, it results into a better approximation of bibliographical author cocitation, 2) since sociocognitive ties analysis can utilize various links not only coauthor networks, diverse kinds of social connections can be found, 3) merging intellectual ties and sociocognitive ties analyses detect gatekeepers who bridges research fields on social networks.
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