# Which Review Aspect Has a Greater Impact on the Duration of Open Peer Review in Multiple Rounds? -- Evidence from Nature Communications

arXiv: https://arxiv.org/abs/2606.21904 · HTML: https://mlsanity.com/paper/2606.21904/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 61 references that are in the map.
- First posted on arXiv 20 Jun 2026.

## Builds on (most cited first, 16 of 16)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [A Dataset of Peer Reviews (PeerRead): Collection, Insights and NLP Applications](https://mlsanity.com/paper/1804.09635/) (2018)
- [Interactive Attention Networks for Aspect-Level Sentiment Classification](https://mlsanity.com/paper/1709.00893/) (2017)
- [Aspect Level Sentiment Classification with Deep Memory Network](https://mlsanity.com/paper/1605.08900/) (2016)
- [ReviewRobot: Explainable Paper Review Generation based on Knowledge Synthesis](https://mlsanity.com/paper/2010.06119/) (2020)
- [Attentional Encoder Network for Targeted Sentiment Classification](https://mlsanity.com/paper/1902.09314/) (2019)
- [Argument Mining for Understanding Peer Reviews](https://mlsanity.com/paper/1903.10104/) (2019)
- [Aspect Level Sentiment Classification with Attention-over-Attention Neural Networks](https://mlsanity.com/paper/1804.06536/) (2018)
- [Aspect-based Sentiment Analysis of Scientific Reviews](https://mlsanity.com/paper/2006.03257/) (2020)
- [Argument Mining Driven Analysis of Peer-Reviews](https://mlsanity.com/paper/2012.07743/) (2020)
- [It's Time to Do Something: Mitigating the Negative Impacts of Computing Through a Change to the Peer Review Process](https://mlsanity.com/paper/2112.09544/) (2021)
- [Textual analysis of artificial intelligence manuscripts reveals features associated with peer review outcome](https://mlsanity.com/paper/1911.02648/) (2019)
- [Which structure of academic articles do referees pay more attention to?: perspective of peer review and full-text of academic articles](https://mlsanity.com/paper/2209.01841/) (2022)
- [Are the confidence scores of reviewers consistent with the review content? Evidence from top conference proceedings in AI](https://mlsanity.com/paper/2505.15031/) (2025)
- [Exploratory analysis of text duplication in peer-review reveals peer-review fraud and paper mills](https://mlsanity.com/paper/2202.03310/) (2022)
- [Review times in peer review: quantitative analysis of editorial workflows](https://mlsanity.com/paper/1508.01134/) (2015)

## Built on by (most cited first, 1 of 1)

- [Aspect-Based Sentiment Evolution and its Correlation with Review Rounds in Multi-Round Peer Reviews: A Deep Learning Approach](https://mlsanity.com/paper/2606.24188/) (2026)

## Abstract (arXiv)

Purpose: Peer review is essential to scientific publishing, but increasing submission volumes have placed growing pressure on reviewers and editors. This study examines the relationship between sentiment toward specific review aspects and peer review duration. It also investigates how this relationship varies across disciplines and review rounds, with the aim of supporting targeted manuscript revision and improving review efficiency. Design/methodology/approach: We adopt a two-stage approach. First, fine-grained aspects are extracted from peer review reports, and a sentiment classification model is used to determine the sentiment associated with each aspect. Second, correlations between aspect-level sentiment and peer review duration are analyzed. Sentiment scores are also calculated for different review rounds to determine whether these relationships change over successive rounds. Findings: Review sentiment has a weak but statistically significant negative correlation with peer review duration, indicating that more positive reviews tend to be associated with shorter review periods. Aspects concerning Evaluation and Results and Impact and Research Value show relatively stronger correlations with review duration. The relationships between aspect-level sentiment and review duration also differ significantly across review rounds. Originality/value: This study connects the textual content of peer review reports with the temporal characteristics of the review process. By identifying review aspects that are more closely associated with review duration, it provides evidence that may help authors prioritize revisions and assist reviewers and editors in improving review efficiency. The findings contribute to reducing the burden of peer review and accelerating scholarly communication and knowledge dissemination.