中国科技期刊研究 ›› 2026, Vol. 37 ›› Issue (2): 201-208. doi: 10.11946/cjstp.202511031339

论坛 上一篇    下一篇

基于不同审稿决策情境的作者反馈行为分析——以F1000Research平台为例

颜兆萍()(), 项波, 石进*()()   

  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 210023
  • 收稿日期:2025-11-03 修回日期:2026-02-01 出版日期:2026-02-25 发布日期:2026-04-01
  • 通讯作者: 石进
  • 作者简介:

    颜兆萍(ORCID: 0000-0001-8198-5574),博士研究生,E-mail:

    项 波,博士研究生。

    颜兆萍:提出研究思路,设计研究方案,撰写论文; 项 波:设计研究方案,论文最终版本修订; 石 进:论文最终版本修订。
  • 基金资助:
    国家自然科学基金项目“面向多模态金融数据要素可信安全高效流通的关键技术研究”(U25A20426); 南京大学中国移动联合研究院项目“数据要素流通领域隐私保护与安全技术研究”(NJ20250043)

Analysis of author feedback behavior in different peer review decision-making scenarios: taking the F1000research platform as an example

YAN Zhaoping()(), XIANG Bo, SHI Jin()()   

  1. School of Information Management,Nanjing University,163 Xianlin Avenue,Qixia District,Nanjing 210023,China
  • Received:2025-11-03 Revised:2026-02-01 Online:2026-02-25 Published:2026-04-01
  • Contact: SHI Jin

摘要:

目的 系统剖析了评审互动中的作者反馈行为,为作者提供策略性回复的实践参考,并深化对同行评议互动机制的理解。 方法 以开放同行评议平台F1000Research为研究对象,围绕作者在不同审稿决策情境下的反馈行为展开定量分析。利用机器学习和统计分析的方法从语言特征维度、文本内容维度和作者反馈重点3个方面对作者反馈内容进行深入分析。通过构建logistic回归模型,进一步分析作者反馈行为对审稿人决策的潜在作用机制。 结果 研究表明,以积极的态度修改有较大概率逆转审稿人决定。作者的回复情感态度与礼貌程度对审稿人态度转变具有显著影响。在逆转审稿人决策态度的作者回复中,对于研究设计和研究对象的完善是打动审稿人的关键所在。 结论 对作者反馈行为的分析能够揭示不同审稿决策情境下的反馈特征与审稿决策之间的关系,不仅为作者提供了有效的反馈策略,还为期刊优化审稿流程、提升评审效率提供了实践指导。

关键词: 作者反馈行为, 同行评议, 审稿决策, 开放平台

Abstract:

Purposes This study systematically analyzes author feedback behavior in peer review interactions, providing practical references for authors to strategically respond and deepening our understanding of the mechanisms of peer review interaction. Methods Taking the open peer review platform F1000Research as the research object, a quantitative analysis was conducted on author feedback behavior under different peer review decision-making scenarios. Machine learning and statistical analysis methods were used to conduct in-depth analysis of author feedback content from three aspects: linguistic features, text content, and the focus of author feedback. A logistic regression model is constructed to further analyze the potential mechanisms by which author feedback behavior influences reviewer decision-making. Findings The results indicate that positive revisions have a significant potential to reverse reviewer attitudes. The author’s sentiment and politeness in the response have a significant impact on the reviewers’ attitude change. In author responses that reverse reviewers’ decision, improvements related to research design and research subjects emerge as the most influential factors in persuading reviewers. Conclusions Analyzing author feedback behavior reveals the relationship between feedback characteristics and peer review decisions under different review decision-making scenarios. This not only provides authors with effective feedback strategies but also offers practical guidance for journals to optimize their review processes and improve review efficiency.

Key words: Author feedback behavior, Peer review, Review decision-making, Open platform