Article (Scientific journals)
Innovation Networks from Inter-organizational Research Collaborations
Esmaeilzadeh Dilmaghani, Saharnaz; Piyatumrong, Apivadee; Danoy, Grégoire et al.
2020In Heuristics for Optimization and Learning, p. 361-375
Peer reviewed
 

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Abstract :
[en] We consider the problem of automatizing network generation from inter-organizational research collaboration data. The resulting networks promise to obtain crucial advanced insights. In this paper, we propose a method to convert relational data to a set of networks using a single parameter, called Linkage Threshold (LT). To analyze the impact of the LT-value, we apply standard network metrics such as network density and centrality measures on each network produced. The feasibility and impact of our approach are demonstrated by using a real-world collaboration data set from an established research institution. We show how the produced network layers can reveal insights and patterns by presenting a correlation matrix.
Disciplines :
Computer science
Author, co-author :
Esmaeilzadeh Dilmaghani, Saharnaz ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > PCOG
Piyatumrong, Apivadee ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC)
Danoy, Grégoire  ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
Bouvry, Pascal ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Computer Science (DCS)
Brust, Matthias R. ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > PCOG
External co-authors :
yes
Language :
English
Title :
Innovation Networks from Inter-organizational Research Collaborations
Publication date :
16 December 2020
Journal title :
Heuristics for Optimization and Learning
Publisher :
Springer, Cham
Pages :
361-375
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
Available on ORBilu :
since 25 January 2021

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