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- Publisher Website: 10.1007/s11192-011-0463-1
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Article: Evolutionary dynamics of scientific collaboration networks: Multi-levels and cross-time analysis
Title | Evolutionary dynamics of scientific collaboration networks: Multi-levels and cross-time analysis |
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Authors | |
Keywords | Co-authorship analysis Dynamic network analysis Evolutionary collaboration networks Multi-levels and cross-time analysis Social network analysis |
Issue Date | 2011 |
Citation | Scientometrics, 2011, v. 89 n. 2, p. 687-710 How to Cite? |
Abstract | Several 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 Identifier | http://hdl.handle.net/10722/194329 |
ISSN | 2023 Impact Factor: 3.5 2023 SCImago Journal Rankings: 1.079 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Abbasi, A | - |
dc.contributor.author | Hossain, L | - |
dc.contributor.author | Uddin, S | - |
dc.contributor.author | Rasmussen, KJR | - |
dc.date.accessioned | 2014-01-30T03:32:27Z | - |
dc.date.available | 2014-01-30T03:32:27Z | - |
dc.date.issued | 2011 | - |
dc.identifier.citation | Scientometrics, 2011, v. 89 n. 2, p. 687-710 | - |
dc.identifier.issn | 0138-9130 | - |
dc.identifier.uri | http://hdl.handle.net/10722/194329 | - |
dc.description.abstract | Several 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.language | eng | - |
dc.relation.ispartof | Scientometrics | - |
dc.subject | Co-authorship analysis | - |
dc.subject | Dynamic network analysis | - |
dc.subject | Evolutionary collaboration networks | - |
dc.subject | Multi-levels and cross-time analysis | - |
dc.subject | Social network analysis | - |
dc.title | Evolutionary dynamics of scientific collaboration networks: Multi-levels and cross-time analysis | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1007/s11192-011-0463-1 | - |
dc.identifier.scopus | eid_2-s2.0-80053953432 | - |
dc.identifier.volume | 89 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 687 | - |
dc.identifier.epage | 710 | - |
dc.identifier.isi | WOS:000296473400012 | - |
dc.identifier.issnl | 0138-9130 | - |