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ReAct: A Review Comment Dataset for Actionability (and more)

International Conference on Web Information Systems Engineering (WISE 2021)

Published October 28, 2021

Gautam Choudhary, Natwar Modani, Nitish Maurya

Review comments play an important role in the evolution of documents. For a large document, the number of review comments may become large, making it difficult for the authors to quickly grasp what the comments are about. It is important to identify the nature of the comments to identify which comments require some action on the part of document authors, along with identifying the types of these comments. In this paper, we introduce an annotated review comment dataset ReAct. The review comments are sourced from OpenReview site. We crowd-source annotations for these reviews for actionability and type of comments. We analyze the properties of the dataset and validate the quality of annotations. We release the dataset to the research community as a major contribution (Full dataset available at https://github.com/gtmdotme/ReAct). We also benchmark our data with standard baselines for classification tasks and analyze their performance.

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