Finding Cross-Border Collaborative Centres in Biopharma Patent Networks: A Clustering Comparison Approach Based on Adjusted Mutual Information

Zhu, Zhen and Gao, Yuan (2021) Finding Cross-Border Collaborative Centres in Biopharma Patent Networks: A Clustering Comparison Approach Based on Adjusted Mutual Information. In: Complex Networks and Their Applications X - Proceedings of the 10th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2021. Studies in Computational Intelligence. Springer, ESP, pp. 62-72. ISBN 978-3-030-93408-8

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Abstract

The recent speedy development of COVID-19 mRNA vaccines has underlined the importance of cross-border patent collaboration. This paper uses the latest edition of the REGPAT database from the OECD and constructs the co-applicant patent networks for the fields of biotechnology and pharmaceuticals. We identify the cross-border collaborative regional centres in these patent networks at NUTS3 level using a clustering comparison approach based on adjusted mutual information (AMI). In particular, we measure and compare the AMI scores of the clustering before and after arbitrarily removing cross-border links of a focal node against the default clustering defined by national borders. The region with the largest difference in AMI scores is identified as the most cross-border collaborative centre, hence the name of our measure, AMI gain. We find that our measure both correlates with and has advantages over the traditional measure betweenness centrality and a simple measure of foreign share.

Item Type: Book Section
Uncontrolled Keywords: patent networks,cross-border,adjusted mutual information,clustering comparison,adjusted mutual information,clustering comparison,cross-border,patent networks,artificial intelligence,sdg 3 - good health and well-being ,/dk/atira/pure/subjectarea/asjc/1700/1702
Faculty \ School: Faculty of Social Sciences > School of Economics
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Depositing User: LivePure Connector
Date Deposited: 06 Jan 2022 15:30
Last Modified: 21 Jun 2022 13:30
URI: https://ueaeprints.uea.ac.uk/id/eprint/82914
DOI: 10.1007/978-3-030-93409-5_6

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