Advances in Science Visualization: Social Networks, Semantic Maps, and Discursive Knowledge

Positional and relational perspectives on network data have led to two different research traditions in textual analysis and social network analysis, respectively. Latent Semantic Analysis (LSA) focuses on the latent dimensions in textual data; social network analysis (SNA) on the observable networks. The two coupled topographies of information-processing in the network space and meaning-processing in the vector space operate with different (nonlinear) dynamics. The historical dynamics of information processing in observable networks organizes the system into instantiations; the systems dynamics, however, can be considered as self-organizing in terms of fluxes of communication along the various dimensions that operate with different codes. The development over time adds evolutionary differentiation to the historical integration; a richer structure can process more complexity. * In preparation for: Pp. 167-185 in: Blaise Cronin and Cassidy R. Sugimoto (Eds.), Beyond Bibliometrics: Harnessing Multidimensional Indicators of Scholarly Impact. Cambridge MA/ London, UK: the MIT Press.