On time-varying collaboration networks

Abstract

The patterns of scientific collaboration have been frequently investigated in terms of complex networks without reference to time evolution. In the present work, we derive collaborative networks (from the arXiv repository) parameterized along time. By defining the concept of affine group, we identify several interesting trends in scientific collaboration, including the fact that the average size of the affine groups grows exponentially, while the number of authors increases as a power law. We were therefore able to identify, through extrapolation, the possible date when a single affine group is expected to emerge. Characteristic collaboration patterns were identified for each researcher, and their analysis revealed that larger affine groups tend to be less stable.

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• Topological-collaborative approach for disambiguating authors' names in collaborative networks
• Contagion processes on the static and activity driven coupling networks
• Robustness of community structure to node removal
• Scale-free collaboration networks: An author name disambiguation perspective
• Extractive Multi Document Summarization using Dynamical Measurements of Complex Networks
• Author Name Disambiguation via Heterogeneous Network Embedding from Structural and Semantic Perspectives
• K-method of calculating the mutual influence of nodes in a directed weight complex networks