-
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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- Journal of the Association for Information Science and Technology. 75(2023) no.1, S.59-78
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Bennett, C.H.; Li, M.; Ma, B.: ¬Die Evolution der Kettenbriefe (2004)
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- Spektrum der Wissenschaft. 2004, H.1, S.78-83
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Kirchherr, W.; Li, M.; Vitányi, P.: ¬The miraculous universal distribution (1997)
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Chen, Z.; Wenyin, L.; Zhang, F.; Li, M.; Zhang, H.: Web mining for Web image retrieval (2001)
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Li, M.; Li, H.; Zhou, Z.-H.: Semi-supervised document retrieval (2009)
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Gu, D.; Liu, H.; Zhao, H.; Yang, X.; Li, M.; Lian, C.: ¬A deep learning and clustering-based topic consistency modeling framework for matching health information supply and demand (2024)
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- Journal of the Association for Information Science and Technology. 75(2023) no.2, S.152-166
