Do you want to read the rest of this article? Request full-text |
See all ›
35 CitationsSee all ›
6 ReferencesSee all ›
4 FiguresRETRACTED: Social networks of author–coauthor relationships
Abstract
This article has been retracted: please see Elsevier Policy on Article Withdrawal (http://www.elsevier.com/locate/withdrawalpolicy).This article has been retracted at the request of the Editor-in-Chief and co-Editors, as it contain portions of other authors' writings on the same topic in other publications, without sufficient attribution to these earlier works being given. The principal authors of the paper acknowledged that text from background sources was mistakenly used in the Introduction without proper reference to the original source. Specifically, the first page and a half of the article (pp. 2177–2178) contain together excerpts from Wikipedia (first paragraph), Wasserman and Faust's “Social Network Analysis: Methods and Applications” (pp. 17–20) ISBN 10: 0-521-38707-8; ISBN 13: 978-0-521-38707-1. Publication Date: 1994, and W. de Nooy, A. Mrvar and V. Bategelj's “Exploratory Social Network Analysis with Pajek"” (pp. 31, 36, 123, and 133) ISBN 10: 0-521-60262-9; ISBN 13: 978-0-521-60262-4. Publication Date: 2005.The scientific community takes a strong view on this matter and apologies are offered to readers of the journal that this was not detected during the submission process.One of the conditions of submission of a paper for publication is that authors declare explicitly that their work is original and has not appeared in a publication elsewhere. The re-use of material, without appropriate reference, even if not known to the authors at the time of submission, breaches our publishing policies.
Figures
- CitationsCitations35
- ReferencesReferences6
- "ty of the small-world model, is: H 1 : The co-authorship networks in the Slovenian scientific community have a high clustering level driven by transitive closure processes where co-authors of co-authors become, or remain, co-authors. The idea of cumulative advantage implies that excellent scientists are rewarded far more than others in their field. Said et al. (2008) noted one factor affecting co-authorship ties is the mentor-student relationship: young researchers are more likely to form new co-authorship ties with older, established researchers, usually their mentors. The formal modelling of cumulative advantage in terms of preferential attachment as the driving mechanism of co-authorship was exam"
[Show abstract] [Hide abstract] ABSTRACT: This paper examines the collaboration structures and dynamics of the co-authorship network of all Slovenian researchers. Its goal is to identify the key factors driving collaboration and the main differences in collaboration behavior across scientific fields and disciplines. Two approaches to modelling network dynamics are combined in this paper: the small-world model and the mechanism of preferential attachment, also known as the process of cumulative advantage. Stochastic-actor-based modelling of co-authorship network dynamics uses data for the complete longitudinal co-authorship networks for the entire Slovenian scientific community from 1996 to 2010. We confirmed the presence of clustering in all fields and disciplines. Preferential attachment is far more complex than a single global mechanism. There were two clear distinctions regarding collaboration within scientific fields and disciplines. One was that some fields had an internal national saturation inhibiting further collaboration. The second concerned the differential impact of collaboration with scientists from abroad on domestic collaboration. In the natural, technical, medical, and biotechnical sciences, this promotes collaboration within the Slovenian scientific community while in the social sciences and humanities this inhibits internal collaboration.- "Research on collaboration network was started with the pioneer work of Newman (2001). After that, a large number of research works have been conducted on the statistical analysis of collaboration network (Ding 2011; Kronegger et al. 2012; Martinez-Romo et al. 2008; Said et al. 2008) and modeling collaboration network through simulations (Huang et al. 2008; Liu et al. 2012; Tambayong 2007 ). Similarly, few related researches on collaboration network, namely developing author-ranking scheme through ''supportiveness'' analysis (Han et al. 2009 ), ego-centric network analysis of collaboration network (Abbasi et al. 2012), classifying personal names through collaboration network (Biryukov 2008 ), discovering the relationship between authors and research domains (Hassan and Ichise 2009), understanding and modeling diverse scientific careers of researchers (Chakraborty et al. 2015 ) etc. have been conducted. "
[Show abstract] [Hide abstract] ABSTRACT: Collaboration networks are elegant representations for studying the dynamical processes that shape the scientific community. In this paper, we are particularly interested in studying the local context of a node in collaboration network that can help explain the behavior of an author as an individual within the group and a member along with the group. The best representation of such local contextual substructures in a collaboration network are “network motifs”. In particular, we propose two fundamental goodness measures of such a group represented by a motif—productivity and longevity. We observe that while 4-semi clique motif, quite strikingly, shows highest longevity, the productivity of the 4-star and the 4-clique motifs is the largest among all the motifs. Based on the productivity distribution of the motifs, we propose a predictive model that successfully classifies the highly cited authors from the rest. Further, we study the characteristic features of motifs and show how they are related with the two goodness measures. Building on these observations, finally we propose two supervised classification models to predict, early in a researcher’s career, how long the group where she belongs to will persist (longevity) and how much the group would be productive. Thus this empirical study sets the foundation principles of a recommendation system that would forecast how long lasting and productive a given collaboration could be in future.- "A network is highly centralized if there is a clear boundary between the center and the periphery. In a highly centralized network, information spreads easily, but the center is indispensable for the transmission of information " (Said, et al, 2008). " The status of an actor is usually expressed in terms of its centrality, i.e., a measure of how central the actor is to the network graph. "
[Show abstract] [Hide abstract] ABSTRACT: This research examines the association between co-authorship network centrality (degree, closeness, betweenness, eigenvector, Bonacich flow betweenness) and productivity of Information science researchers. The research population includes all those researchers who have published at least one record in one of the twenty journals of Information Science which has an impact factor of 0.635 as a minimum from the years 1996 to 2010. By using social network analyses, this study examines information science researchers’ outputs during 1996-2011 in ISI Web of Science database. In general co-authorship network of these researchers was analyzed by UCINET6 software. Results showed that there is a significant correlation between Journal Impact Factor (JIF) and all centrality measures except closeness centrality at P= 0.001. Results also showed that there is a significant correlation between productivity of authors and all centrality measures scores at P≥ 0.001. Also, regression reports direct relationship of degree, closeness and flow betweenness and inverse relationship of betweenness as well as Eigen vector centrality on productivity of researchers. Keywords: Co-authorship; Network centrality; Scientific productivity; Social network analysis, Journal Impact Factor
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.
This publication is from a journal that may support self archiving.
Learn more