什么造就了计算机科学会议中成功的反驳？：社会互动视角
What makes a successful rebuttal in computer science conferences? : A perspective on social interaction
AI总结：
本研究以ICLR2022的3000余篇论文、13000余份审稿意见为样本，从社会互动视角分析了计算机科学会议成功反驳的影响因素，验证了相关策略与特征的作用，为反驳相关研究奠定了基础。
摘要：
随着顶级计算机科学（CS）会议投稿量呈指数级增长，越来越多的会议在同行评审流程中引入了反驳阶段。反驳阶段可被建模为作者与审稿人之间的社会互动，成功的反驳通常会使反驳阶段后的审稿评分得到提升。本文开展了一项实证研究，以计算机科学领域最负盛名的会议之一ICLR2022的3000余篇论文和13000余份审稿意见为样本，探究促成成功反驳的因素。首先，我们观察到反驳阶段前后的审稿评分存在显著差异，这一差异对论文录用至关重要。此外，我们采用有符号社会网络分析，从审稿人视角探究相关影响因素，一个值得注意的发现是反驳阶段后平衡网络结构的占比有所提升。随后，我们评估了若干可量化的作者反驳策略及其对审稿评分的影响，这些策略可帮助作者提升审稿评分。最后，我们使用机器学习模型预测反驳成功率，并验证了本文所分析的潜在因素的影响。实验表明，利用本研究提出的所有特征可助力预测反驳的成功与否。综上，本工作从审稿人和作者双视角研究了成功反驳的影响因素，为采用社会网络分析开展反驳相关研究奠定了基础。
英文摘要：
With an exponential increase in submissions to top-tier Computer Science (CS) conferences, more and more conferences have introduced a rebuttal stage to the conference peer review process. The rebuttal stage can be modeled as social interactions between authors and reviewers. A successful rebuttal often results in an increased review score after the rebuttal stage. In this paper, we conduct an empirical study to determine the factors contributing to a successful rebuttal using over 3,000 papers and 13,000 reviews from ICLR2022, one of the most prestigious computer science conferences. First, we observe a significant difference in review scores before and after the rebuttal stage, which is crucial for paper acceptance. Furthermore, we investigate factors from the reviewer's perspective using signed social network analysis. A notable finding is the increase in balanced network structure after the rebuttal stage. Subsequently, we evaluate several quantifiable author rebuttal strategies and their effects on review scores. These strategies can help authors in improving their review scores. Finally, we used machine learning models to predict rebuttal success and validated the impact of potential factors analyzed in this paper. Our experiments demonstrate that the utilization of all features proposed in this study can aid in predicting the success of the rebuttal. In summary, this work presents a study on the impact factors of successful rebuttals from both reviewers' and authors' perspectives and lays the foundation for analyzing rebuttals with social network analysis.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
