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Thelwall, M.; Kousha, K.; Abdoli, M.; Stuart, E.; Makita, M.; Wilson, P.; Levitt, J.: Why are coauthored academic articles more cited : higher quality or larger audience? (2023)
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- Date
- 22. 6.2023 18:11:50
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Wang, S.; Ma, Y.; Mao, J.; Bai, Y.; Liang, Z.; Li, G.: Quantifying scientific breakthroughs by a novel disruption indicator based on knowledge entities : On the rise of scrape-and-report scholarship in online reviews research (2023)
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- 22. 1.2023 18:37:33
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Zhang, Y.; Wu, M.; Zhang, G.; Lu, J.: Stepping beyond your comfort zone : diffusion-based network analytics for knowledge trajectory recommendation (2023)
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- 22. 6.2023 18:07:12
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Manley, S.: Letters to the editor and the race for publication metrics (2022)
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- Date
- 6. 4.2022 19:22:26
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Liu, M.; Bu, Y.; Chen, C.; Xu, J.; Li, D.; Leng, Y.; Freeman, R.B.; Meyer, E.T.; Yoon, W.; Sung, M.; Jeong, M.; Lee, J.; Kang, J.; Min, C.; Zhai, Y.; Song, M.; Ding, Y.: Pandemics are catalysts of scientific novelty : evidence from COVID-19 (2022)
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Lorentzen, D.G.: Bridging polarised Twitter discussions : the interactions of the users in the middle (2021)
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- Date
- 20. 1.2015 18:30:22
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Milard, B.; Pitarch, Y.: Egocentric cocitation networks and scientific papers destinies (2023)
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- Date
- 21. 3.2023 19:22:14
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Cerda-Cosme, R.; Méndez, E.: Analysis of shared research data in Spanish scientific papers about COVID-19 : a first approach (2023)
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- Abstract
- During the coronavirus pandemic, changes in the way science is done and shared occurred, which motivates meta-research to help understand science communication in crises and improve its effectiveness. The objective is to study how many Spanish scientific papers on COVID-19 published during 2020 share their research data. Qualitative and descriptive study applying nine attributes: (a) availability, (b) accessibility, (c) format, (d) licensing, (e) linkage, (f) funding, (g) editorial policy, (h) content, and (i) statistics. We analyzed 1,340 papers, 1,173 (87.5%) did not have research data. A total of 12.5% share their research data of which 2.1% share their data in repositories, 5% share their data through a simple request, 0.2% do not have permission to share their data, and 5.2% share their data as supplementary material. There is a small percentage that shares their research data; however, it demonstrates the researchers' poor knowledge on how to properly share their research data and their lack of knowledge on what is research data.
- Date
- 21. 3.2023 19:22:02
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- e
-
Fang, Z.; Dudek, J.; Costas, R.: Facing the volatility of tweets in altmetric research (2022)
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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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Thelwall, M.; Thelwall, S.: ¬A thematic analysis of highly retweeted early COVID-19 tweets : consensus, information, dissent and lockdown life (2020)
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- Date
- 20. 1.2015 18:30:22
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Asubiaro, T.V.; Onaolapo, S.: ¬A comparative study of the coverage of African journals in Web of Science, Scopus, and CrossRef (2023)
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- Date
- 22. 6.2023 14:09:06
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Vakkari, P.; Järvelin, K.; Chang, Y.-W.: ¬The association of disciplinary background with the evolution of topics and methods in Library and Information Science research 1995-2015 (2023)
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- Date
- 22. 6.2023 18:15:06
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Kulczycki, E.; Huang, Y.; Zuccala, A.A.; Engels, T.C.E.; Ferrara, A.; Guns, R.; Pölönen, J.; Sivertsen, G.; Taskin, Z.; Zhang, L.: Uses of the Journal Impact Factor in national journal rankings in China and Europe (2022)
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Thelwall, M.; Kousha, K.; Abdoli, M.; Stuart, E.; Makita, M.; Wilson, P.; Levitt, J.: Do altmetric scores reflect article quality? : evidence from the UK Research Excellence Framework 2021 (2023)
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Ikae, C.; Savoy, J.: Gender identification on Twitter (2022)
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