Mapping leadership and communities in EU-funded research through network analysis

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ID: 281938
2024
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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 collaboration patterns. The case study reveals key leaders and stable communities within the hydrogen energy sector, providing valuable insights for policymakers and organisations fostering innovation through sustained collaborations. The proposed methodology effectively identifies influential organisations and tracks the stability of research collaborations. The insights gained are valuable for policymakers and organisations seeking to foster innovation through sustained partnerships. This approach can be extended to other sectors, offering a framework for understanding the impact of EU research funding on collaboration and leadership dynamics.
Reference Key
stefano2024mapping Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Fabio Morea; Alberto Soraci; Domenico De Stefano
Journal arXiv
Year 2024
DOI
DOI not found
URL
http://arxiv.org/abs/2410.19556v1
Keywords
cs.si

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