基于增强型引文数据的期刊诊断性评价研究——以《中国科技期刊研究》为例

【目的】 深入挖掘引文数据在期刊评价中的价值,帮助期刊从宏观和微观层面识别自身的优势和不足,制定个性化影响力提升策略。【方法】 提出一种基于增强型引文数据的期刊诊断性评价方法,采用引文增强方法增强期刊的发文、施引及被引数据,从学科与研究主题两个方面开展期刊诊断性评价,以《中国科技期刊研究》为例进行实证研究。【结果】 利用增强型引文数据可以客观分析期刊对不同学科的影响力大小及稳定程度,并通过探讨期刊的热点追踪能力、主题输出能力、学术引领能力综合评价期刊内容影响力,评估期刊在各学科和研究主题领域中所处的地位及发挥的作用。【结论】 增强型引文数据拥有比传统引文数据更为丰富的语义信息,可以很好地支持细粒度、多维度的期刊影响力评价。

Diagnostic evaluation of journal based on augmented citation data: Taking Chinese Journal of Scientific and Technical Periodicals as an example

[Purposes] This paper aims to deeply explore the value of citation data in journal evaluation to help journals identify their strengths and weaknesses from the macro and micro levels and develop personalized influence-promoting strategies. [Methods] This paper proposed a diagnostic evaluation method for journals based on augmented citation data. The citation augmentation method was used to augment the publication, citation, and cited data of journals. Taking Chinese Journal of Scientific and Technical Periodicals as an example, we carried out academic influence evaluation of journals from two aspects of disciplines and research topics. [Findings] Using augmented citation data, we objectively analyze the level and stability of the journal's influence on different disciplines and comprehensively evaluate its content influence by discussing the journal's hotspot tracking ability, topic output ability, and academic leading ability, to judge the position and role of the journal in different disciplines and different research fields. [Conclusions] Augmented citation data have richer semantic information than traditional citation data, which can well support the fine-grained and multi-dimensional journal influence evaluation.