结合引文内容分析数据的科技期刊影响力评价研究

【目的】参考二维度融合的期刊影响力评价模型,探索利用人工智能引文内容分析平台——Scite.ai所提供的数据,结合传统引文指标开展科技期刊的影响力评价。【方法】以Web of Science数据库中耳鼻喉科学分类下收录的国际期刊为研究对象,对期刊的8项传统引文指标和5项引文内容分析指标,采用归一化处理、相关性分析、信度分析、效度分析和因素分析方法,分析期刊通过传统引文指标表现出来的宏观影响力和通过引文内容分析指标表现出来的微观影响力,最后融合两类影响力得到二维评价结果。【结果】8项传统引文指标之间的正相关性极显著,指标整体的一致性也较高;5项引文内容分析指标中,4项指标之间的正相关性极显著,引文支持型占比指标(Scite Index,SI)与其余4项指标不具有相关性,不适合单独用于期刊影响力评价;两类影响力间的相关性系数为0.492,呈中度正相关,引文内容分析指标可以作为传统引文指标评价体系的有益补充。【结论】由于不具有相关性,Scite.ai所提供的SI指标不适合单独用于期刊影响力评价;利用传统引文指标进行期刊影响力评价时有必要结合Scite.ai平台的其他引文内容分析指标以全面反映期刊的学术质量。

Impact evaluation of scientific journals based on citation content analysis data and citation indicators

Purposes] Combining the citation content analysis data deprived from Scite.ai platform and the traditional citation indicators, this paper investigates the method of evaluating the academic influence of scientific journals. Methods] Taking 42 international otorhinolaryngology journals as cases, combining 8 traditional citation indicators and 5 citation content analysis indicators, we used the method of multi-indicator fusion to construct a comprehensive evaluation model of journal impact. Through normalization processing, correlation analysis, reliability analysis, validity analysis, and factor analysis, we evaluated the macroscopical impact (F_macro) and microscopical impact (F_micro) of otorhinolaryngology journals respectively. Findings] It is found that 8 traditional citation indicators present strong positive correlations, and the indicators are highly consistent overall and internally. There are high positive correlations among 4 citation indicators based on Scite.ai platform, and the SI (Scite Index) does not have correlation with the other 4 citation indicators. The correlation coefficient between F_macro and F_micro is 0.492, with a moderate positive correlation. It indicates that the evaluation of otolaryngology journals' microscopical impact based on Scite.ai indicators is a useful supplement to the evaluation of academic impact based on traditional citation. Conclusions] The indicator SI is not appropriate for evaluating journal impact solely due to its week correlations with other Scite.ai indicators. It makes sense to combine the traditional citation indicators and citation content analysis data to evaluate academic impact.