Network topologies, power laws, and hierarchy
ACM SIGCOMM Computer Communication Review
Global information technology: A meta analysis of key issues
Information and Management
Visualizing and tracking the growth of competing paradigms: two case studies
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
More Than an Answer: Information Relationships for Actionable Knowledge
Organization Science
Journal of Management Information Systems
Social network, social trust and shared goals in organizational knowledge sharing
Information and Management
Large Scale Structure and Dynamics of Complex Networks: From Information Technology to Finance and Natural Science
A social network-empowered research analytics framework for project selection
Decision Support Systems
CSCW in the healthcare enterprise: a knowledge domain visualization
Proceedings of the companion publication of the 17th ACM conference on Computer supported cooperative work & social computing
A local social network approach for research management
Decision Support Systems
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New concepts and ideas build on older ones. This path dependence in knowledge evolution has promoted research to identify important knowledge elements, research trends, and opportunities by analyzing publication data. In our study, keyword networks formed from published academic articles were analyzed to examine how keywords are associated with each other and to identify important keywords and their change over time. Based on MIS publication data from 1999 to 2008, our analysis provided several notable findings. First, while the MIS field has changed rapidly, resulting in many new keywords, the connectivity among them is highly clustered. Second, the keyword networks show clear power-law distribution, which implies that the more popular a keyword, the more likely it is selected by new researchers and used in follow-on studies. In addition, a strong hierarchical structure is identified in the network. Third, the network-based perspective reveals interdisciplinary keywords which are different from popular ones and have the potential to lead research in the MIS field.