Mapping leadership and communities in EU-funded research through network analysis
Fabio Morea, Alberto Soraci, Domenico De Stefano

TL;DR
This paper presents a network analysis methodology to map collaboration patterns, leadership roles, and community structures in EU-funded research projects, exemplified by the North Adriatic Hydrogen Valley case study.
Contribution
It introduces a novel approach using open Horizon data to analyze collaboration networks, addressing biases and variability for reliable insights into research leadership and community stability.
Findings
Identified key influential organisations in hydrogen energy sector
Mapped stable research communities over time
Provided insights for policymakers to foster innovation
Abstract
Horizon 2020 and Horizon Europe the EU programs supporting research and innovation through collaboration between companies, academic institutions, and research organisations. This paper introduces a novel methodology using open data on Horizon programs to analyse collaborations, leadership roles, and their evolution, with a focus on the North Adriatic Hydrogen Valley project in the hydrogen energy sector. The methodology employs network analysis, transforming tabular data into weighted networks that represent collaborations between organisations. Centrality measures and community detection algorithms identify influential organisations and stable partnerships over time. To ensure robust and reliable results, the methodology addresses challenges such as input-ordering bias and result variability, while the exploration of the solution space enhances the accuracy of identified…
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Taxonomy
TopicsEvaluation and Performance Assessment
