Open Review Based Dataset

Open review-based datasets are collections of scientific papers and their associated reviews, used to analyze the peer-review process and improve automated text analysis. Current research focuses on leveraging these datasets to develop and evaluate models for tasks such as review quality assessment, spam detection, and aspect-based sentiment analysis, often employing deep neural networks like transformers (e.g., BERT, RoBERTa) and Siamese networks. These datasets are valuable resources for advancing natural language processing techniques and improving the efficiency and fairness of scientific evaluation, with applications ranging from automated review assistance to enhanced customer feedback analysis.