摘要：

【目的】 探索运用科研管理分析工具SciVal助力期刊编辑及时发现研究热点、个性化选题及精准约稿的方法。【方法】 以2016—2019年肿瘤领域论文为研究对象,基于SciVal的全域微观概念模型创建组稿专题,根据主题显著度遴选热点专题;根据SciVal的海量作者学术画像快速遴选肿瘤领域的国内外组稿专家。【结果】 SciVal为肿瘤领域的选题策划提供全球基准数据,包括肿瘤领域全球研究热点52个,最新研究热点6个,肿瘤领域高影响力专家20位,核心学术团队4个。【结论】 通过SciVal的文献数据挖掘技术来提炼研究热点并发掘核心团队的方法,可为期刊编辑的选题和组稿提供多元化的方法支持,也为大数据时代期刊的高质量发展提供有效途径。

关键词: 文献计量学, 选题, 组稿, SciVal

Abstract:

[Purposes] This paper uses the scientific research management analysis tool SciVal to help journal editors to discover research hotspots in real time, so as to carry out personalized topic selection and precise solicitation of contributions. [Methods] Taking the oncology papers published from 2016 to 2019 as the research objects, we created a topic on solicitation of contributions based on the global-micro conceptual model in SciVal, and selected the topics on hotspots according to the prominence. At the same time, we quickly selected experts on solicitation of contributions in the field of oncology according to the massive author academic portraits in SciVal. [Findings] SciVal provides global benchmark data for topic selection in the field of oncology, including 52 global research hotspots, 6 latest research hotspots, 20 high-impact experts, and 4 core academic teams. [Conclusions] The method, which uses SciVal-based literature data mining technology to refine research hotspots and discover the core team, provides a variety of methodological support for journal editors in topic selection and solicitation of contributions, and provides an effective way for journals to move towards high-quality development in the era of big data.

Key words: Bibliometrics, Topic selection, Solicitation of contribution, SciVal