学术论文创新质量评价研究——以多能干细胞技术为例  

Evaluating Innovation Quality of Academic Papers——Case Study of Pluripotent Stem Cells

作　　者：汪雪锋[1] 于慧妍 郑思佳 雷鸣 Wang Xuefeng;Yu Huiyan;Zheng Sijia;Lei Ming(School of Management,Beijing Institute of Technology,Beijing 100081,China)

机构地区：[1]北京理工大学管理学院,北京100081

出　　处：《数据分析与知识发现》2024年第5期127-138,共12页Data Analysis and Knowledge Discovery

基　　金：国家自然科学基金面上项目(项目编号:72074020)的研究成果之一。

摘　　要：【目的】通过构建学术论文创新质量评价模型,探讨基于定量与定性相结合的科技评价方法,促进科学研究的渐进性创新。【方法】兼顾创新新颖性和影响性特征,采用Doc2Vec算法将非结构化文本内容转化为向量空间模型,继而运用余弦相似度测度文本内容相似度,同时应用待评价论文局部引文网络构建创新影响指数计算方法,并将新颖性和影响性测度结果映射到二维散点图中,基于区域划分构建学术论文创新质量评价模型。【结果】多能干细胞技术实证结果显示:本文方法与F1000推荐结果基本一致,能够在一定程度上弥补当前学术论文创新质量评价的不足。【局限】仅讨论了学术论文新颖性、学术论文创新影响两个因素,存在一定的片面性。【结论】本文构建的评价模型能够为定性的同行评议提供定量数据支撑,是对学术论文创新质量定量评价的有益探索。[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.

关 键 词：创新质量 新颖性 颠覆性指数 Doc2Vec算法 多能干细胞 

分 类 号：G353[文化科学—情报学]