学术论文创新质量评价研究——以多能干细胞技术为例

[Objective] This study constructs an evaluation model for academic paper innovation quality. It explores a new method combining quantitative and qualitative approaches and promotes the progressive innovation of scientific research. [Methods] Balancing the innovative novelty and impact characteristics, we utilized the Doc2Vec algorithm to convert unstructured textual content into a vector space model. Then, we used cosine similarity to measure text content’s similarity. Simultaneously, we constructed a calculation method for the innovation impact index using the local citation network of the paper under evaluation. Third, we mapped the novelty and impact measurements onto a two-dimensional scatter plot. Finally, we constructed a model for evaluating the innovation quality of academic papers based on regional division. [Results] Empirical results on pluripotent stem cell technology showed that the proposed method is consistent with the F1000 recommendation results and can partly compensate for the deficiencies in the current evaluation of the innovation quality of academic papers. [Limitations] We only discussed the impacts of academic papers’novelty and innovation. There are many other factors influencing the quality of academic paper innovation. [Conclusions] Our new model can provide quantitative data support for qualitative peer review and represents a beneficial exploration of quantitative evaluation of the innovation quality of academic papers.