This research will identify the factors that lead to the formation, maintenance and dissolution of dynamically linked knowledge networks. Two core research questions will be addressed: How do diverse knowledge networks co-evolve over time and at multiple levels? How do the centrality, density, diffusion and other properties of knowledge networks at each level affect task performance by individuals, groups and organizations? The PIs plan to adopt a broad, generic approach to understanding the co-evolution of knowledge networks. Knowledge networks may share important common structural properties across levels, or may develop in similar ways. Where that proves to be true, theories at one level can be expanded to apply to networks at several levels; where network properties diverge, existing theories will be modified and new ones developed. The theory generated by this research, the computational models tested and the statistical techniques developed will have important scientific implications beyond the substantive research findings of this project; they will be applicable to human networks in other contexts as well as to a variety of knowledge and network issues in society, and will also significantly enhance future statistical analysis of many forms of networks.
