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Li, J.; Shi, D.: Sleeping beauties in genius work : when were they awakened? (2016)
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- Date
- 22. 1.2016 14:13:32
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Zhao, S.X.; Zhang, P.L.; Li, J.; Tan, A.M.; Ye, F.Y.: Abstracting the core subnet of weighted networks based on link strengths (2014)
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- Abstract
- Most measures of networks are based on the nodes, although links are also elementary units in networks and represent interesting social or physical connections. In this work we suggest an option for exploring networks, called the h-strength, with explicit focus on links and their strengths. The h-strength and its extensions can naturally simplify a complex network to a small and concise subnetwork (h-subnet) but retains the most important links with its core structure. Its applications in 2 typical information networks, the paper cocitation network of a topic (the h-index) and 5 scientific collaboration networks in the field of "water resources," suggest that h-strength and its extensions could be a useful choice for abstracting, simplifying, and visualizing a complex network. Moreover, we observe that the 2 informetric models, the Glänzel-Schubert model and the Hirsch model, roughly hold in the context of the h-strength for the collaboration networks.
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Zhu, Q.; Kong, X.; Hong, S.; Li, J.; He, Z.: Global ontology research progress : a bibliometric analysis (2015)
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- Date
- 20. 1.2015 18:30:22
17. 9.2018 18:22:23
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Liu, X.; Bu, Y.; Li, M.; Li, J.: Monodisciplinary collaboration disrupts science more than multidisciplinary collaboration (2024)
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- Abstract
- Collaboration across disciplines is a critical form of scientific collaboration to solve complex problems and make innovative contributions. This study focuses on the association between multidisciplinary collaboration measured by coauthorship in publications and the disruption of publications measured by the Disruption (D) index. We used authors' affiliations as a proxy of the disciplines to which they belong and categorized an article into multidisciplinary collaboration or monodisciplinary collaboration. The D index quantifies the extent to which a study disrupts its predecessors. We selected 13 journals that publish articles in six disciplines from the Microsoft Academic Graph (MAG) database and then constructed regression models with fixed effects and estimated the relationship between the variables. The findings show that articles with monodisciplinary collaboration are more disruptive than those with multidisciplinary collaboration. Furthermore, we uncovered the mechanism of how monodisciplinary collaboration disrupts science more than multidisciplinary collaboration by exploring the references of the sampled publications.
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Shi, D.; Rousseau, R.; Yang, L.; Li, J.: ¬A journal's impact factor is influenced by changes in publication delays of citing journals (2017)
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Xie, Z.; Ouyang, Z.; Li, J.; Dong, E.: Modelling transition phenomena of scientific coauthorship networks (2018)
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- Editor
- Yi, D.
