Which Is More Helpful in Finding Scientific Papers to Be Top-cited in the Future: Content or Citations? Case Analysis in the Field of Solar Cells 2009
Which Is More Helpful in Finding Scientific Papers to Be Top-cited in the Future: Content or Citations? Case Analysis in the Field of Solar Cells 2009
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DOI：
10.5220/0010689100003058
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发表时间：
2021
期刊：
影响因子：
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通讯作者：
Masanao Ochi;M. Shiro;Junichiro Mori;I. Sakata
中科院分区：
文献类型：
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作者：
Masanao Ochi;M. Shiro;Junichiro Mori;I. Sakata
随着科学文献数字化出版的增加和研究的碎片化，越来越难找到有前途的论文。当然，我们可以查看大量论文的内容，但更容易查看引用的参考文献。因此，我们想知道一篇论文是否有前途，仅仅基于它的内容和引文信息。本文提出了一种将论文的内容和引文作为分布式表示进行提取和聚类，并使用相同的标准进行比较的方法。这种方法澄清了未来有希望的论文是偏向于内容还是偏向引用。我们通过比较三年后成为被引用最多的论文在2009年发表的论文中的分布情况来评估所提出的方法。结果发现，与内容信息相比，引文信息更容易识别出未来被引次数最多的论文39.9%。这一分析将为开发更通用的模型以早期预测各种科学研究和科学技术趋势的影响提供基础。
With the increasing digital publication of scientific literature and the fragmentation of research, it is becoming more and more difficult to find promising papers. Of course, we can examine the contents of a large number of papers, but it is easier to look at the references cited. Therefore, we want to know whether a paper is promising or not based only on its content and citation information. This paper proposes a method of extracting and clustering the content and citations of papers as distributed representations and comparing them using the same criteria. This method clarifies whether the future promising papers will be biased toward content or citations. We evaluated the proposed method by comparing the distribution of the papers that would become the top-cited papers three years later among the papers published in 2009. As a result, we found that the citation information is 39.9% easier to identify the papers that will be the top-cited papers in the future than the content information. This analysis will provide a basis for developing more general models for early prediction of the impact of various scientific researches and trends in science and technology.