基于Altmetrics的学术论文影响力评价模型研究——以人工智能领域为例  

Evaluation Model of Academic Papers Impact Based on Altmetrics:A Case Study of the Field of Artifi cial Intelligence

作　　者：韩童茜 许鑫 HAN Tongqian;XU Xin(Department of Information Management,Faculty of Economics and Management,East China Normal University,Shanghai 200241,China)

机构地区：[1]华东师范大学经济与管理学部信息管理系,上海200241

出　　处：《文献与数据学报》2020年第1期68-79,共12页Journal of Library and Data

摘　　要：[目的/意义]构建基于Altmetrics的学术论文影响力评价模型,分析新模型特点,为挖掘高价值学术论文提供新途径。[方法/过程]获取Web of Science中2017年人工智能领域论文的Altmetrics指标数据,探索Altmetrics指标特点和指标间关系,以人工智能领域的实证数据为基础构建评价模型。[结果/结论]Altmetrics指标覆盖率不高;与高WoS被引频次论文相比,高Altmetrics评价得分论文之间的联系更为密切,研究内容更集中,更能挖掘内容之间的关系。[Purpose/significance]This paper aims to construct an influence evaluation model of academic papers based on Altmetrics,analyzes the characteristics of the new model,and provides a new way for mining high-value academic papers.[Method/process]This paper obtains the Altmetrics index data of the 2017 papers in the fi eld of Artifi cial Intelligence in Web of Science and explores the characteristics of Altmetrics indicators,the relationships between the indicators.The empirical data in the fi eld of Artifi cial Intelligence is used to build an evaluation model.[Result/conclusion]This paper fi nds that Altmetrics index coverage is not high;compared with highly cited WoS papers,the papers with high Altmetrics Evaluation Score are more closely connected,their research content is more concentrated,and the relationships between their content are easier to explore.

关 键 词：Altmetrics 学术论文影响力 评价模型 人工智能 

分 类 号：G255[文化科学—图书馆学]