Data-driven modeling of collaboration networks: a cross-domain analysis

@article{Tomasello2017DatadrivenMO,
  title={Data-driven modeling of collaboration networks: a cross-domain analysis},
  author={Mario V. Tomasello and Giacomo Vaccario and Frank Schweitzer},
  journal={EPJ Data Science},
  year={2017},
  volume={6},
  pages={1-25}
}
  • Mario V. Tomasello, Giacomo Vaccario, Frank Schweitzer
  • Published 2017
  • Computer Science, Physics
  • EPJ Data Science
  • We analyze large-scale data sets about collaborations from two different domains: economics, specifically 22,000 R&D alliances between 14,500 firms, and science, specifically 300,000 co-authorship relations between 95,000 scientists. Considering the different domains of the data sets, we address two questions: (a) to what extent do the collaboration networks reconstructed from the data share common structural features, and (b) can their structure be reproduced by the same agent-based model. In… CONTINUE READING
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