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

@article{citeulike:4205833, 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.}, author = {Ma, Ruimin and Dai, Qiangbin and Ni, Chaoqun and Li, Xuelu}, citeulike-article-id = {4205833}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/s11192-009-2063-x}, citeulike-linkout-1 = {http://www.springerlink.com/content/f2wg100412467351}, doi = {10.1007/s11192-009-2063-x}, journal = {Scientometrics}, keywords = {china, citation, google, scholar, scientometrics}, posted-at = {2009-03-30 10:22:26}, priority = {2}, title = {An author co-citation analysis of information science in China with Chinese Google Scholar search engine, 2004–2006}, url = {http://dx.doi.org/10.1007/s11192-009-2063-x} }

TY - JOUR ID - citeulike:4205833 L3 - citeulike-article-id:4205833 N2 - 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. JF - Scientometrics TI - An author co-citation analysis of information science in China with Chinese Google Scholar search engine, 2004–2006 KW - china KW - citation KW - google KW - scholar KW - scientometrics AU - Ma, Ruimin AU - Dai, Qiangbin AU - Ni, Chaoqun AU - Li, Xuelu UR - http://dx.doi.org/10.1007/s11192-009-2063-x ER -