Analysis of a Planetary Scale Scientific Collaboration Dataset Reveals Novel Patterns
Soumya Banerjee

TL;DR
This paper analyzes a large scientific collaboration dataset to identify patterns and clusters among countries, revealing insights into how collaboration networks differ between developed and impoverished nations and proposing a dynamical model to explain these behaviors.
Contribution
It introduces a novel dynamical model and comprehensive analysis of a global scientific collaboration network, highlighting patterns and differences among countries based on economic status.
Findings
Identified clusters of countries with distinct collaboration characteristics.
Developed a dynamical model explaining changes in collaboration networks over time.
Revealed patterns reflecting geopolitical influences on scientific collaboration.
Abstract
Scientific collaboration networks are an important component of scientific output and contribute significantly to expanding our knowledge and to the economy and gross domestic product of nations. Here we examine a dataset from the Mendeley scientific collaboration network. We analyze this data using a combination of machine learning techniques and dynamical models. We find interesting clusters of countries with different characteristics of collaboration. Some of these clusters are dominated by developed countries that have higher number of self connections compared with connections to other countries. Another cluster is dominated by impoverished nations that have mostly connections and collaborations with other countries but fewer self connections. We also propose a complex systems dynamical model that explains these characteristics. Our model explains how the scientific collaboration…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComplex Network Analysis Techniques
