论文标题
在期刊网络中检测异常引文组
Detecting anomalous citation groups in journal networks
论文作者
论文摘要
学术出版市场中不断增强的竞争力激励期刊编辑追求更高的影响因素。这转化为期刊变得更加选择性,并最终成为更高的出版标准。但是,对较高影响因素的固定使一些期刊通过日记的“引用卡特尔”的协调工作来人为地增强影响因素。近年来,“引用卡特尔”行为变得越来越普遍,其中有一些实例报道。在这里,我们提出了一种算法(名为Cidre),以检测异常的期刊群体,这些期刊与占科学社区和期刊规模的无效模型相比,以过高的速率交换引用。 CIDRE检测到一半以上的期刊因暂停或事先暂停一年中的异常引用行为而被暂停的期刊引文报告。此外,CIDRE检测到许多新的异常群体,在这些群体中,通过其他成员期刊的引用,会员期刊的影响因素更高。我们详细介绍了许多此类示例,并讨论了我们关于当前学术环境的发现的含义。
The ever-increasing competitiveness in the academic publishing market incentivizes journal editors to pursue higher impact factors. This translates into journals becoming more selective, and, ultimately, into higher publication standards. However, the fixation on higher impact factors leads some journals to artificially boost impact factors through the coordinated effort of a "citation cartel" of journals. "Citation cartel" behavior has become increasingly common in recent years, with several instances being reported. Here, we propose an algorithm -- named CIDRE -- to detect anomalous groups of journals that exchange citations at excessively high rates when compared against a null model that accounts for scientific communities and journal size. CIDRE detects more than half of the journals suspended from Journal Citation Reports due to anomalous citation behavior in the year of suspension or in advance. Furthermore, CIDRE detects many new anomalous groups, where the impact factors of the member journals are lifted substantially higher by the citations from other member journals. We describe a number of such examples in detail and discuss the implications of our findings with regard to the current academic climate.