中国科技期刊研究 ›› 2023, Vol. 34 ›› Issue (12): 1593-1600. doi: 10.11946/cjstp.202305100338

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引入Altmetrics指标的掠夺性期刊识别研究

汪林梓()(), 章博昕, 陈铭*()()   

  1. 南京大学信息管理学院,江苏省南京市栖霞区仙林大道163号 210046
  • 收稿日期:2023-05-10 修回日期:2023-09-18 出版日期:2023-12-15 发布日期:2024-01-10
  • 通讯作者: *陈铭(ORCID:0000-0001-5061-6821),博士,副教授,硕士生导师,E-mail: chenming@nju.edu.cn。
  • 作者简介:

    汪林梓(ORCID:0009-0009-9092-5915),硕士研究生,E-mail:;

    章博昕,硕士研究生。

    作者贡献声明:
    汪林梓:设计研究思路,收集整理数据,撰写及修改论文;
    章博昕:收集整理数据,撰写及修改论文;
    陈铭:设计研究思路,撰写及修改论文。
  • 基金资助:
    江苏高校哲学社会科学研究重大项目“开放环境下学术期刊的信誉风险预警研究”(2022SJZD093)

Predatory journal identification using Altmetrics metrics

WANG Linzi()(), ZHANG Boxin, CHEN Ming()()   

  1. School of Information Management, Nanjing University, 163 Xianlin Avenue, Qixia District, Nanjing 210046, China
  • Received:2023-05-10 Revised:2023-09-18 Online:2023-12-15 Published:2024-01-10

摘要:

【目的】 探讨将Altmetrics指标应用于掠夺性期刊识别的效果,为掠夺性期刊的识别提供新视角。【方法】 基于Logit回归模型,分别构造仅含平均被引频次、仅含Altmetrics存在率指标以及同时融合这两个指标的3个掠夺性期刊判别模型,并通过ROC曲线对3个模型的拟合效果进行比较。使用邀请投稿邮件中的期刊数据对模型效果进行验证。【结果】 同时融合平均被引频次和Altmetrics存在率的掠夺性期刊判别模型效果最优,两个指标与期刊掠夺性均显著负相关。以使用邮件邀请投稿的14种期刊数据验证发现,超过85%的期刊被识别为掠夺性期刊,说明模型的合理性。【结论】 Altmetrics指标在掠夺性期刊的识别中具有良好的效果,为掠夺性期刊识别提供有益补充。

关键词: 掠夺性期刊, Altmetrics, 被引频次, Logit模型, 识别研究

Abstract:

[Purposes] This article explores the effect of introducing the Altmetrics index into the identification of predatory journals, so as to provide a new perspective for the identification of predatory journals. [Methods] Based on the Logit regression model, three models for the identification of predatory journals were constructed using the single average cited frequency, single presence rate of Altmetrics, and a combination of both indicators. The ROC curve was used to compare the fitting effects of the three models. Finally, journal data in invitation emails were used to validate the model effects. [Findings] The model integrating both average cited frequency and presence rate of Altmetrics performs the best for identifying predatory journals, with both indicators showing a significant negative correlation with journal predatoriness. Validation using the data from 14 journals in invitation emails shows that over 85% of them are identified as predatory journals by the model, demonstrating the rationality of the model. [Conclusions] The application of the Altmetrics metric has shown good results and provides valuable supplements in the identification of predatory journals.

Key words: Predatory journal, Altmetrics, Cited frequency, Logit model, Identification study