What makes a successful rebuttal in computer science conferences?: A perspective on social interaction

Junjie Huang, Win-Bin Huang, Yi Bu, Qi Cao, Huawei Shen, Xueqi Cheng

Abstract: Highlights•In this paper, we aim to identify the factors contributing to a successful rebuttal in computer science conferences, which is an interesting research problem in informetrics.•We model the rebuttal stage as social interactions between authors and reviewers, analyzing the impact factors from both reviewers’ and authors’ perspectives.•From the reviewers’ perspective, one prominent finding is that the balanced network structure increased after the rebuttal stage in several real-world datasets.•From the authors’ perspective, we verify several quantifiable author rebuttal strategies that can help authors improve their chances of a successful rebuttal.•We define and conduct rebuttal success prediction using machine learning models to demonstrate that the utilization of proposed features.