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README.md
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path: data/validation-*
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---
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path: data/validation-*
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---
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# OATS Dataset
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## Description
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The OATS (Opinion Aspect Target Sentiment) dataset is a comprehensive collection designed for the Aspect Sentiment Quad Prediction (ASQP) or Aspect-Category-Opinion-Sentiment (ACOS) task. This dataset aims to facilitate research in aspect-based sentiment analysis by providing detailed opinion quadruples extracted from review texts. Additionally, for each review, we offer tuples summarizing the dominant sentiment polarity toward each aspect category discussed.
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The dataset covers three distinct domains: Amazon FineFood reviews, Coursera course reviews, and TripAdvisor Hotel reviews, offering a broad spectrum for analysis across different types of services and products.
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Structure
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The dataset is structured into two primary components:
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Opinion Quadruples: Detailed annotations on the level of individual opinions, including the aspect, the sentiment target, and the corresponding sentiment.
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Review-Level Tuples: Aggregate information at the review level, indicating the overall sentiment polarity for each aspect category mentioned.
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## Domains
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Amazon FineFood Reviews
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Coursera Course Reviews
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TripAdvisor Hotel Reviews
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Each domain is annotated from scratch, ensuring high-quality data for nuanced sentiment analysis tasks.
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Citation
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If you use the OATS dataset in your research, please cite the original authors:
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```
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@misc{chebolu2023oats,
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title={OATS: Opinion Aspect Target Sentiment Quadruple Extraction Dataset for Aspect-Based Sentiment Analysis},
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author={Siva Uday Sampreeth Chebolu and Franck Dernoncourt and Nedim Lipka and Thamar Solorio},
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year={2023},
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eprint={2309.13297},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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## Usage
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This dataset has been curated to facilitate easy access and integration into existing NLP pipelines. To use this dataset, you can load it using the datasets library by Hugging Face:
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```
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from datasets import load_dataset
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dataset = load_dataset("jordiclive/OATS-ABSA")
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```
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