中国科技期刊研究 ›› 2022, Vol. 33 ›› Issue (5): 591-595. doi: 10.11946/cjstp.202111030857

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英文科技期刊论文图片学术不端审读方法探索与思考

叶青()()   

  1. 浙江大学出版社《浙江大学学报(英文版)》编辑部,浙江省杭州市西湖区天目山路148号 310028
  • 收稿日期:2021-11-03 修回日期:2022-04-10 出版日期:2022-05-15 发布日期:2022-06-22
  • 作者简介:叶 青(ORCID:0000-0002-6681-4731),博士,副编审,E-mail: jzus_yq@zju.edu.cn
  • 基金资助:
    中国科学院自然科学期刊编辑研究会研究课题“英文期刊论文图片学术不端审读方法研究”(YJHWT202108);中国科技期刊卓越行动计划(C137)

A method for detecting image manipulations in English academic journals

YE Qing()()   

  1. Editorial Office of Journal of Zhejiang University-SCIENCE, Zhejiang University Press, 148 Tianmushan Road, Xihu District, Hangzhou 310028, China
  • Received:2021-11-03 Revised:2022-04-10 Online:2022-05-15 Published:2022-06-22

摘要:

【目的】 尝试通过针对图片不当处理检测方法的实践,提出明确的图片检测规范和具体的检测标准。【方法】 通过梳理近年来图片学术不端典型案例的特征,使用Photoshop、Droplets及Forensically三种计算机辅助识别工具,在期刊日常工作的不同阶段进行图片不当处理检测,以完善图片不当处理的检测方法。【结果】 构建并完善图片不当处理的检测方法和判断分级标准,并在论文发表前和发表后,分别检测到有3.2%和1.3%的论文存在图片不当处理。【结论】 期刊编辑部应提高对图片不当处理的重视,并加强对作者关于正确处理图片的引导,期刊主管部门则应注重对期刊学术伦理的建设。

关键词: 科技期刊, 学术不端, 图片篡改, 不当处理, 检测

Abstract:

[Purposes] We use different methods to detect image manipulations and thereby put forward clear image detection specifications and standards in English academic journals. [Methods] We summarized the characteristics of typical cases of image manipulations in recent years and used computer-aided identification tools, such as Photoshop, Droplets, and Forensically, to detect image manipulations at different stages of article processing, aiming to improve the detection method of image manipulations. [Findings] The detection method and judging criteria for image manipulations were developed and improved, with which image manipulation was detected in 3.2% and 1.3% of the papers before and after publication, respectively. [Conclusions] Journals should emphasize the image manipulation and guide the correct processing of images, and the competent department of journals should strengthen the ethical construction of journals.

Key words: Scientific journal, Academic misconduct, Image manipulation, Misconduct, Detection