基于<bold>Altmetrics</bold>的睡美人文献特征与唤醒研究

doi:10.3772/j.issn.1000-0135.2023.11.002

情报学报

2023, Vol. 42

Issue (11): 1276-1288 DOI: 10.3772/j.issn.1000-0135.2023.11.002

情报理论与方法

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基于Altmetrics的睡美人文献特征与唤醒研究

向菲¹, 曹广², 沈桐^1,3, 陈华芳¹

1.华中科技大学同济医学院医药卫生管理学院,武汉 430030
2.浙江省人民医院,杭州 310014
3.华中科技大学同济医学院附属同济医院,武汉 430030

Features and Awakening of Sleeping Beauties Based on Altmetrics

Xiang Fei¹, Cao Guang², Shen Tong^1,3, 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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摘要睡美人文献具有重要价值，在确定了睡美人文献的识别方法后，应该对睡美人文献的特征、睡眠原因和唤醒过程进行分析，以期找到实现睡美人文献早期识别的线索。以关注度排名前1%的文献形成实验数据集，选取ASB指数（Altmetrics sleeping beauty index）作为睡美人文献的识别方法。计算实验数据集的ASB值，选取ASB值最高的10篇文章作为睡美人文献代表，对这10篇文章的多项特征和关注累积过程进行详细分析，归纳睡美人文献的文献特征和唤醒规律。睡美人文献内容主要可以归为两类：首创型文献和经典案例型文献，文献涉及内容均是日常生活中频繁出现的话题且文献内容质量较高。通过文献特征分析可以发现，非开放存取、无资助的文献更有可能成为睡美人文献，文献内容复杂、超出公众知识理解水平时容易陷入睡眠。睡美人文献被唤醒的主要原因有：①读者知识水平的提高；②相似问题的出现；③与公众事件相关；④有影响力的账号推荐等。实现睡美人文献的早期识别，可以多关注首创型或经典案例型文献、在Patent或Wikipedia平台获得关注的文献、非开放存取或无资助的文献。使用社交媒体平台的学术用户，在实现睡美人文献早期识别方面具有重要作用。

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	向菲
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关键词 ：社交媒体, Altmetrics, 睡美人文献, 文献特征, 唤醒

收稿日期: 2022-09-27

基金资助:中央高校基本科研业务费资助项目“基于Altmetrics的睡美人文献识别方法与唤醒机制研究”（HUST：2021WKYXZX007）。

作者简介: 向菲，男，1981年生，博士，副教授，硕士生导师，主要研究领域为卫生信息管理、在线健康社区、文献计量学；曹广，男，1994年生，硕士，主要研究领域为情感分析、在线健康社区；沈桐，男，1997年生，硕士，主要研究领域为健康医疗大数据；陈华芳，通信作者，女，1997年生，硕士，主要研究领域为卫生信息管理、替代计量学，E-mail：1006995503@qq.com；

引用本文:

向菲, 曹广, 沈桐, 陈华芳. 基于Altmetrics的睡美人文献特征与唤醒研究[J]. 情报学报, 2023, 42(11): 1276-1288.
Xiang Fei, Cao Guang, Shen Tong, Chen Huafang. Features and Awakening of Sleeping Beauties Based on Altmetrics. 情报学报, 2023, 42(11): 1276-1288.

链接本文:

https://qbxb.istic.ac.cn/CN/10.3772/j.issn.1000-0135.2023.11.002 或 https://qbxb.istic.ac.cn/CN/Y2023/V42/I11/1276

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