An author co-citation analysis of information science in China with Chinese Google Scholar search engine, 2004–2006

This paper conducts ACA of information science in China with the Chinese Google Scholar, selecting 31 most important authors of informationScience in China as research objects and employing Pajek, a powerful tool in social network analysis, to visualize the author co-citation matrix.

Abstract

Abstract Author co-citation analysis (ACA) is an important method for discovering the intellectual structure of a given scientific field. Since traditional ACA was confined to ISI Web of Knowledge (WoK), the co-citation counts of pairs of authors mainly depended on the data indexed in WoK. Fortunately, Google Scholar has integrated different academic databases from different publishers, providing an opportunity of conducting ACA in wider a range. In this paper, we conduct ACA of information science in China with the Chinese Google Scholar. Firstly, a brief introduction of Chinese Google Scholar is made, including retrieval principles and data formats. Secondly, the methods used in our paper are given. Thirdly, 31 most important authors of information science in China are selected as research objects. In the part of empirical study, factor analysis is used to find the main research directions of information science in China. Pajek, a powerful tool in social network analysis, is employed to visualize the author co-citation matrix as well. Finally, the resemblances and the differences between China and other countries in information science are pointed out.