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| Features and Awakening of Sleeping Beauties Based on Altmetrics |
| Xiang Fei1, Cao Guang2, Shen Tong1,3, Chen Huafang1 |
1.School of Medicine and Health Management, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430030
2.Zhejiang Provincial People’s Hospital, Hangzhou 310014
3.Tongji Hospital, Tongji Medical College of Huazhong University of Science and Technology, Wuhan 430030 |
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Abstract It has been shown that Altmetrics-based “sleeping beauties” (A-SBs) are of great value. After developing methods to identify A-SBs, we must analyze the features, sleep causes, and awakening laws of A-SBs to realize their early prediction. This research considered the articles with the top 1% of attention as its experimental data and ASB index as the identification method. To explore the literature features and awakening laws of A-SBs, this research took the 10 articles with the highest ASB values as representative A-SBs and analyzed their features and attention accumulation processes in detail. The content of A-SBs is of high quality and can be divided into two categories, innovation and classic, and their topics frequently appear in daily life. Non-open-access or non-funded articles are more likely to become A-SBs. With complex content that is beyond the knowledge level of the general public, an article has more possibilities to fall asleep. The reasons for A-SBs being awakened include (1) improvement of the public’s knowledge, (2) encountering similar problems, (3) related public events, and (4) influential account recommendations. For the early prediction of A-SBs, it is helpful to pay more attention to innovative or classic articles, articles that gained attention on Patent or Wikipedia, non-open access articles, or non-funded articles. Scholars who use social media play an important role in realizing the early prediction of A-SBs.
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Received: 27 September 2022
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