Comparative study on methods of detecting research fronts using different types of citation
Comparative study on methods of detecting research fronts using different types of citation
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DOI：
10.1002/asi.v60:3
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发表时间：
2009-03
影响因子：
3.5
通讯作者：
N. Shibata;Y. Kajikawa;Y. Takeda;K. Matsushima
中科院分区：
文献类型：
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作者：
N. Shibata;Y. Kajikawa;Y. Takeda;K. Matsushima
在这篇文章中，我们进行了一项比较研究，以调查用于检测新兴研究前沿的方法的性能。三种类型的引文网络，共引，书目耦合，和直接引用，在三个研究领域，氮化镓（GaN），复杂网络（CNW），和碳纳米管（CNT）进行了测试。为每个研究领域构建了三种类型的引文网络，并将这些领域的论文划分为聚类，以检测研究前沿。我们通过使用以下指标来评估每种类型的引文网络在检测研究前沿方面的性能：可见性，以归一化的聚类大小衡量，速度，以平均出版年份衡量，拓扑相关性，以密度衡量。直接引用可以更早地发现大型和年轻的新兴集群，在检测研究前沿方面表现最好，而共同引用表现最差。此外，在直接引用网络中，聚类系数是最大的，这表明直接引用连接的论文的内容相似性是最大的，直接引用网络具有最小的风险，错过新兴的研究领域，因为核心论文包括在最大的组件。© 2009威利期刊公司.
In this article, we performed a comparative study to investigate the performance of methods for detecting emerging research fronts. Three types of citation network, co-citation, bibliographic coupling, and direct citation, were tested in three research domains, gallium nitride (GaN), complex network (CNW), and carbon nanotube (CNT). Three types of citation network were constructed for each research domain, and the papers in those domains were divided into clusters to detect the research front. We evaluated the performance of each type of citation network in detecting a research front by using the following measures of papers in the cluster: visibility, measured by normalized cluster size, speed, measured by average publication year, and topological relevance, measured by density. Direct citation, which could detect large and young emerging clusters earlier, shows the best performance in detecting a research front, and co-citation shows the worst. Additionally, in direct citation networks, the clustering coefficient was the largest, which suggests that the content similarity of papers connected by direct citations is the greatest and that direct citation networks have the least risk of missing emerging research domains because core papers are included in the largest component. © 2009 Wiley Periodicals, Inc.