科学论文被引频次预测的现状分析与研究被引量：28

An Analysis and Research on Papers' Citation-counts Prediction

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摘要通过被引频次来判断论文影响力已经得到广泛应用,如何快速而准确地挖掘到有价值的文章,是文献计量学领域的重要探索。对国内外科学论文被引频次的影响因素和预测方法进行了系统归纳,首先从传统文献计量学、新兴网络计量学两方面,将影响论文引用的相关因素按作者因素、文章因素、期刊因素、网络计量学、其他因素这五个维度进行梳理,然后总结了常用的引用预测方法,并重点探讨了回归分析法,最后对影响论文引用因素的选择、数据来源及指标问题进行讨论,并提出相关建议。 Citation-count is widely used in assessing the impact of papers and how to mine the valuable papers quickly and accurately is an urgent exploration in bibliometfics. This paper is aimed to summarize systematically the indicators and prediction methods for scientific pa- pers citation impact. According to the traditional bibliometrics and emerging webmewics, all the factors are classified into paper factors, author factors, journal factors, webmetrics and other factors. Then the methods on predicting citation-count are discussed, focusing on re- gression analysis. Finally, advices about selection of indictors and data sources are presented.

作者鲍玉芳马建霞

机构地区中国科学院兰州文献情报中心中国科学院大学

出处《情报杂志》 CSSCI 北大核心 2015年第5期66-71,共6页 Journal of Intelligence

基金国家自然科学基金项目"基于科学基金项目及知识产出的研究前沿探测"(编号:71373260) 中国科学院西部之光联合学者项目"基于计算情报方法的甘肃省战略新兴产业技术创新竞争与发展研究"(编号:Y200201001)的研究成果之一

关键词科学论文引用被引频次引用预测 scientific papers citation citation count citation prediction

分类号 G350 [文化科学—情报学]

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