论文标题

积极引用在科学评估中的作用

The Role of Positive and Negative Citations in Scientific Evaluation

论文作者

Bai, Xiaomei, Lee, Ivan, Ning, Zhaolong, Tolba, Amr, Xia, Feng

论文摘要

客观地量化科学论文的影响对于研究产出评估至关重要,研究产出评估随后影响机构和国家排名,研究资助分配,学术招聘以及国家/国际科学的优先事项。尽管基于出版引用的大多数评估方案可能通过负引用来操纵,但在这项研究中,我们探索了利益冲突(COI)关系,并发现负面引用并随后削弱了相关的引用强度。已经开发了Pandora(正和负面的目标等级算法),该算法捕获了正面和负COI,以及正面和负面的COI关系。为了减轻负面COI关系,协作时间,协作时间跨度,引用时间和引文时间跨度的影响,用于确定强度;在正面的COI关系中,我们将其视为正常的引文关系。此外,我们基于信用分配算法来计算Pagerank和HITS算法对学术论文的影响,该算法用于公平和客观地评估机构的影响。实验是在美国物理社会(APS)数据集的出版数据集上进行的,结果表明,我们的方法在TOP-K和Spearman在TOP-K的列表R的建议强度大大优于当前的解决方案。

Quantifying the impact of scientific papers objectively is crucial for research output assessment, which subsequently affects institution and country rankings, research funding allocations, academic recruitment and national/international scientific priorities. While most of the assessment schemes based on publication citations may potentially be manipulated through negative citations, in this study, we explore Conflict of Interest (COI) relationships and discover negative citations and subsequently weaken the associated citation strength. PANDORA (Positive And Negative COI- Distinguished Objective Rank Algorithm) has been developed, which captures the positive and negative COI, together with the positive and negative suspected COI relationships. In order to alleviate the influence caused by negative COI relationship, collaboration times, collaboration time span, citation times and citation time span are employed to determine the citing strength; while for positive COI relationship, we regard it as normal citation relationship. Furthermore, we calculate the impact of scholarly papers by PageRank and HITS algorithms, based on a credit allocation algorithm which is utilized to assess the impact of institutions fairly and objectively. Experiments are conducted on the publication dataset from American Physical Society (APS) dataset, and the results demonstrate that our method significantly outperforms the current solutions in Recommendation Intensity of list R at top-K and Spearman's rank correlation coefficient at top-K.

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