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Article: Evolutionary dynamics of scientific collaboration networks: Multi-levels and cross-time analysis

TitleEvolutionary dynamics of scientific collaboration networks: Multi-levels and cross-time analysis
Authors
KeywordsCo-authorship analysis
Dynamic network analysis
Evolutionary collaboration networks
Multi-levels and cross-time analysis
Social network analysis
Issue Date2011
Citation
Scientometrics, 2011, v. 89 n. 2, p. 687-710 How to Cite?
AbstractSeveral studies exist which use scientific literature for comparing scientific activities (e. g., productivity, and collaboration). In this study, using co-authorship data over the last 40 years, we present the evolutionary dynamics of multi level (i. e., individual, institutional and national) collaboration networks for exploring the emergence of collaborations in the research field of "steel structures". The collaboration network of scientists in the field has been analyzed using author affiliations extracted from Scopus between 1970 and 2009. We have studied collaboration distribution networks at the micro-, meso- and macro-levels for the 40 years. We compared and analyzed a number of properties of these networks (i. e., density, centrality measures, the giant component and clustering coefficient) for presenting a longitudinal analysis and statistical validation of the evolutionary dynamics of "steel structures" collaboration networks. At all levels, the scientific collaborations network structures were central considering the closeness centralization while betweenness and degree centralization were much lower. In general networks density, connectedness, centralization and clustering coefficient were highest in marco-level and decreasing as the network size grow to the lowest in micro-level. We also find that the average distance between countries about two and institutes five and for authors eight meaning that only about eight steps are necessary to get from one randomly chosen author to another. © 2011 Akadémiai Kiadó, Budapest, Hungary.
Persistent Identifierhttp://hdl.handle.net/10722/194329
ISSN
2021 Impact Factor: 3.801
2020 SCImago Journal Rankings: 0.999
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorAbbasi, A-
dc.contributor.authorHossain, L-
dc.contributor.authorUddin, S-
dc.contributor.authorRasmussen, KJR-
dc.date.accessioned2014-01-30T03:32:27Z-
dc.date.available2014-01-30T03:32:27Z-
dc.date.issued2011-
dc.identifier.citationScientometrics, 2011, v. 89 n. 2, p. 687-710-
dc.identifier.issn0138-9130-
dc.identifier.urihttp://hdl.handle.net/10722/194329-
dc.description.abstractSeveral studies exist which use scientific literature for comparing scientific activities (e. g., productivity, and collaboration). In this study, using co-authorship data over the last 40 years, we present the evolutionary dynamics of multi level (i. e., individual, institutional and national) collaboration networks for exploring the emergence of collaborations in the research field of "steel structures". The collaboration network of scientists in the field has been analyzed using author affiliations extracted from Scopus between 1970 and 2009. We have studied collaboration distribution networks at the micro-, meso- and macro-levels for the 40 years. We compared and analyzed a number of properties of these networks (i. e., density, centrality measures, the giant component and clustering coefficient) for presenting a longitudinal analysis and statistical validation of the evolutionary dynamics of "steel structures" collaboration networks. At all levels, the scientific collaborations network structures were central considering the closeness centralization while betweenness and degree centralization were much lower. In general networks density, connectedness, centralization and clustering coefficient were highest in marco-level and decreasing as the network size grow to the lowest in micro-level. We also find that the average distance between countries about two and institutes five and for authors eight meaning that only about eight steps are necessary to get from one randomly chosen author to another. © 2011 Akadémiai Kiadó, Budapest, Hungary.-
dc.languageeng-
dc.relation.ispartofScientometrics-
dc.subjectCo-authorship analysis-
dc.subjectDynamic network analysis-
dc.subjectEvolutionary collaboration networks-
dc.subjectMulti-levels and cross-time analysis-
dc.subjectSocial network analysis-
dc.titleEvolutionary dynamics of scientific collaboration networks: Multi-levels and cross-time analysis-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1007/s11192-011-0463-1-
dc.identifier.scopuseid_2-s2.0-80053953432-
dc.identifier.volume89-
dc.identifier.issue2-
dc.identifier.spage687-
dc.identifier.epage710-
dc.identifier.isiWOS:000296473400012-
dc.identifier.issnl0138-9130-

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