A New Metric for the Analysis of the Scientific Article Citation Network
Livia Lin-Hsuan Chang, Frederick Kin Hing Phoa, Junji NakanoCitation plays an important role in the bibliometrics analysis since the introduction of the impact factors, but traditional measures mainly focused on the direct citations between articles. In this work, we introduce a new metric, namely Article Network Influence (ANI), to measure the influence of an article by using broader citation relationships quantitatively. We prepare our article citation networks from one of the largest citation databases called the Web of Science, and we demonstrate the use of ANI on the analysis of these networks in the statistics research community. These analyses appear in the top-20 influential articles in statistics within every 11 years during 1981-2006. We consider differences between the new metric and several traditional measures.