Journal of the American Society for Information Science and Technology (2010)

The Structure and Dynamics of Co-Citation Clusters:

A Multiple-Perspective Co-Citation Analysis

Chaomei Chen¹, Fidelia Ibekwe-SanJuan², Jianhua Hou³

¹College of Information Science and Technology, Drexel University, 3141 Chestnut Street, Philadelphia 19104-2875, U.S.A.

²ELICO, University of Lyon-3. 4 cours Albert Thomas, 69008 Lyon, France.

³WISELAB, Dalian University of Technology, Dalian, China

Preprint version at arXiv

Abstract

A multiple-perspective co-citation analysis method is introduced for characterizing and interpreting the structure and dynamics of co-citation clusters. The method facilitates analytic and sense making tasks by integrating network visualization, spectral clustering, automatic cluster labeling, and text summarization. Co-citation networks are decomposed into co-citation clusters. The interpretation of these clusters is augmented by automatic cluster labeling and summarization. The method focuses on the interrelations between a co-citation cluster’s members and their citers. The generic method is applied to a three-part analysis of the field of Information Science as defined by 12 journals published between 1996 and 2008: 1) a comparative author co-citation analysis (ACA), 2) a progressive ACA of a time series of co-citation networks, and 3) a progressive document co-citation analysis (DCA). Results show that the multiple-perspective method increases the interpretability and accountability of both ACA and DCA networks.

Acknowledgements

This work is supported in part by the National Science Foundation under grant IIS-0612129. We wish to thank Eric SanJuan of the University of Avignon, France, for implementing the Enertex sentence ranking algorithm used in this study; Howard White, Drexel University, USA, for his detailed and constructive comments on an earlier draft; Dangzhi Zhao and Andreas Strotmann of the University of Alberta, Canada, for providing detailed factor loading results of their factor analysis for the comparative ACA and for their comments on an earlier draft of the article; and anonymous reviewers for their detailed reviews. Special thanks to Zeyuan Liu and members of the WISELAB at Dalian University of Technology, China, for their valuable feedback based on their extensive use of earlier versions of CiteSpace.

Supplement Materials

Figures:

Size distributions of ACA clusters

Size distributions of DCA clusters

Tables:

Major specialties of information science identified in previous co-citation studies

Descriptive statistics of the information science dataset (1996-2008)

Distributions of articles and reviews in the 12-journal dataset

Cluster-to-factor mapping in the comparative ACA (2001-2005)

50 co-citation clusters identified in DCA (sorted by size)

Enertex summary of 50 DCA clusters based on positions

Enertex summary 50 DCA clusters