Comparative analysis of coauthorship networks of different domains: The growth and change of networks

Yoshikane, Fuyuki; Kageura, Kyo

doi:10.1023/b:scie.0000034385.05897.46

Cited by 60 publications

(31 citation statements)

References 23 publications

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“…Os resultados de diversos estudos sobre coautoria usando ARS revelam que as colaborações entre pesquisadores têm aumentado em todas as áreas do conhecimento e mostram a importância da coautoria na solidificação da produção científica (YOSHIKANE; KAGEURA, 2004, NEWMAN, 2004BOZEMAN, 2005, MAIA;CAREGNATO, 2008, HAYASHI;HAYASHI;LIMA, 2008;YAN;DING, 2009, ABBASI;HWANG, 2010, GOLDENBERG et al, 2010SOUZA;BARBASTEFANO, 2011, ABBASI;HOSSAIN, 2011, BARBASTEFANO et al, 2013WIGAND;HOSSAIN, 2014; dentre outros).…”

Section: Introductionunclassified

Inferência estatística clássica para a confiabilidade de rede de coautoria com enfoque nos vértices

Oliveira

Ferreira

Brigantini

et al. 2014

Perspect. ciênc. inf.

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Um grupo de pesquisa pode ser considerado uma rede social, a qual pode ser modelada por um grafo G composto por k vértices e m arestas. Os pesquisadores que compõem essa rede podem ser interpretados como seus vértices, e as conexões ou ligações entre esses pesquisadores (representadas por trabalhos em coautoria) podem ser consideradas suas arestas. O objetivo deste trabalho foi estudar a medida de confiabilidade de redes considerando os vértices ou pesquisadores não confiáveis e as arestas ou conexões perfeitamente confiáveis. Especificamente, foi proposta uma abordagem inferencial clássica para a confiabilidade de redes, obtendo os estimadores de máxima verossimilhança e os respectivos intervalos de confiança para os componentes individuais (pesquisadores) e para a rede de coautoria; foi aplicada a metodologia a um grupo de pesquisa da UNESP cadastrado no CNPq; e, foram obtidas medidas de centralidade de vértices para auxiliar na identificação de situações onde a inserção de uma aresta ou ligação entre dois pesquisadores do grupo poderia aumentar significativamente a confiabilidade da rede de coautoria. Os resultados mostraram a utilidade da inferência estatística no contexto de confiabilidade de redes sociais, ressaltando que a contribuição de cada pesquisador é de extrema importância para a manutenção de um grupo de pesquisa. Verificou-se ainda que o cálculo da confiabilidade de uma rede de coautoria pode ser bastante desgastante de ser executado e que as medidas de centralidade são uma ferramenta viável quando se intenciona aumentar a confiabilidade dessa rede.

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Section: Introductionunclassified

Inferência estatística clássica para a confiabilidade de rede de coautoria com enfoque nos vértices

Oliveira

Ferreira

Brigantini

et al. 2014

Perspect. ciênc. inf.

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“…Reviewing literature of scientific research collaboration network on different aggregation level, there are researches on collaborations in different fields on personal level [14], and researches on organizational level, which investigate collaboration inside an organization [15] or cross-organizations [9]. In addition, according to research focus, overall network and individual network researches are included.…”

Section: Related Work and Review 21 Scientific Research Collaboratimentioning

confidence: 99%

Node importance measure for scientific research collaboration from hypernetwork perspective

Xiao

2016

Teh. vjesn.

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Original scientific paper Collaboration has become main stream and trend in interdisciplinary fields. In research collaboration organizations, to evaluate the contributions of researchers to the organization and then to identify core researchers is an important issue to carry out performance appraisal and crisis management of brain drain. Scientific research collaboration network is a basic model to investigate this question, but under the context of increasingly complex collaborative behaviour, it shows its limitations for semantic representations. In this paper, by introducing hypernetwork, a more powerful modelling tool than traditional network, and taking scientific paper co-authorship as object to construct scientific research collaboration hypernetwork (SRCH), we measure the importance of researchers in two aspects, as collaborative relationship structure and collaborative achievement value from a hypernetwork perspective. An additive weighting method with adjustable parameters is utilized to integrate the evaluation indicators of the two aspects, and then the synthetical importance evaluation of researchers is obtained. Analysis of data instance verifies that our node importance measure for scientific research collaboration from hypernetwork perspective is reasonable and effective. Keywords: adjustable parameter; hyper network; node importance; scientific research collaboration network Mjera važnosti čvora u suradnji pri znanstvenom istraživanju sa stajališta hiper mrežeIzvorni znanstveni članak U interdisciplinarnim područjima sve se više pažnje posvećuje međusobnoj suradnji. U organizacijama koje se bave istraživanjem suradnje, od bitne je važnosti evaluirati doprinos istraživača svojoj organizaciji te identificirati glavne istraživače. Mreža suradnje u znanstvenom istraživanju predstavlja osnovni model, ali u kontekstu sve složenijeg suradničkog ponašanja javljaju se problemi oko njegovog semantičkog predstavljanja. U ovom radu, uvođenjem hiper mreže, moćnijeg alata za modeliranje od tradicionalne mreže i uzimajući koautorstvo u znanstvenom radu kao cilj za stvaranje hiper mreže suradnje u znanstvenom istraživanju (scientific research collaboration hypernetwork -SRCH), mjerimo važnost istraživača u dva smjera, kao strukturu suradničkog odnosa i vrijednost postizanja suradnje sa stajališta hiper mreže. Upotrebljena je dodatna metoda mjerenja s prilagodljivim parametrima u svrhu integracije indikatora evaluacije dvaju aspekata te je dobivena procjena sintetičke važnosti istraživača. Analiza rabljenih podataka potvrdila je da je naša mjera važnosti čvora u znanstveno istraživačkoj suradnji sa stajališta hiper mreže razumna i učinkovita. Ključne riječi: hiper mreža; mreža istraživanja suradnje u znanstvenim istraživanjima; prilagodljivi parametar; važnost čvora

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“…To analyze the academic communities and its trends, in particular those related to co-authorship, scientists frequently make use of social network analysis (SNA). The studies include areas such as Biomedical, Physics and Computer Science (NEWMAN, 2001), Biology, Physics, and Mathematics (NEWMAN, 2004), Biotechnology, Mathematics, Physics and Sociology (KRONEGGER; FERLIGOJ; DOREIAN, 2011), Nanoscience, Pharmacology and Statistics (BORDONS et al, 2015), Electrical Engineering, Information Processing, Polymer Science and Biochemistry (YOSHIKANE and KAGEURA, 2004) and Medical (YOUSEFI-NOORAIE et al, 2008) juts to cite a few. A survey on co-authorship networks could be found on Glänzel and Schubert (2004) and Kumar (2015).…”

Section: Introductionmentioning

confidence: 99%

“…Nowadays, scientific collaboration are becoming even more intense (ALEXANDER, 1953) and studies are pointing out that to be more productive, researchers need more partners (YOSHIKANE; KAGEURA, 2004). To analyze the academic communities and its trends, in particular those related to co-authorship, scientists frequently make use of social network analysis (SNA).…”

Section: Introductionmentioning

confidence: 99%

A Co-authorship network analysis of CNPq’s productivity research fellows in the probability and statistic area

Souza

Amorim²,

Rêgo

2016

Perspect. ciênc. inf.

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In this paper, we analyzed the co-authorship network between all CNPq’s productivity research fellows in the Probability and Statistics area in Brazil. Our aim was to describe and to understand how network measures influence researchers’ productivity. The data was gathered from the CNPq’s Lattes Platform using the software scriptLattes, and a link between two fellows represents the fact that they wrote an article together from 2009 to 2013. The network is disconnected and has only 4.7% of its possible connections. Through a regression analysis, we were able to infer that the centrality positions of an author matters to his/her productivity. As expected, closeness centrality had a negative effect on fellows’ productivity, while the degree centrality had a positive effect.

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Comparative analysis of coauthorship networks of different domains: The growth and change of networks

Cited by 60 publications

References 23 publications

Inferência estatística clássica para a confiabilidade de rede de coautoria com enfoque nos vértices

Inferência estatística clássica para a confiabilidade de rede de coautoria com enfoque nos vértices

Node importance measure for scientific research collaboration from hypernetwork perspective

A Co-authorship network analysis of CNPq’s productivity research fellows in the probability and statistic area

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