Life-Cycles and Mutual Effects of Scientific Communities

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Abstract:

Assessment of scientific progress based on citation measures is static. Analysis and modelling of dynamic mutual effects of scientific communities promises to be a more viable form of evaluation of progress and impact of a research community. We propose a general framework uniquely combining topological and content analysis with special visualization techniques to analyse and explain such dynamics.

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