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Analysis of a planetary scale scientific collaboration dataset reveals novel patterns

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 b...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/978-3-319-45901-1_7

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Institution:
University of Oxford
Division:
MPLS
Role:
Author
Publisher:
Springer International Publishing Publisher's website
Journal:
Complex Systems Digital Campus 2015 – World e-Conference, Conference on Complex Systems Journal website
Pages:
85-90
Series:
Springer Proceedings in Complexity
Host title:
Complex Systems Digital Campus 2015 – World e-Conference, Conference on Complex Systems
Publication date:
2016-12-26
Acceptance date:
2016-12-01
DOI:
ISSN:
2213-8684
Source identifiers:
668957
ISBN:
9783319459011
Pubs id:
pubs:668957
UUID:
uuid:e29e24b2-339e-4d76-95ab-ce38e8b418a4
Local pid:
pubs:668957
Deposit date:
2017-01-11

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