Title: A study of the article citation network in statistics research community
Authors: LinHsuan Chang - SOKENDAI (The graduate university for advanced studies) (Taiwan) [presenting]
Junji Nakano - The Institute of Statistical Mathematics (Japan)
Frederick Kin Hing Phoa - Academia Sinica (Taiwan)
Abstract: Web of Science (WoS) database can be viewed as a big multi-layer, multi-level and dynamic network of articles over years. Among all layers of network, we are interested in some implicit phenomena in the article citation network in statistics research community. Our goal is to develop a method which can evaluate the research performance more accurately and can improve the problems of the current evaluation methods. It is clear that the citation network is described by directed graph with special structure according to the published time of articles. We use the theoretical approach to generate the network considering these structures explicitly. Then we introduce a new quantity to measure the importance or influence of an article, in terms of its multi-stage citation structure in the whole network. We undergo a systematic ranking process by using our method for all articles being tagged as statistics in the WoS subject area, identifying which articles are influential in statistics community within 2005-2014.