Datasets:
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---
license: cc-by-nc-4.0
task_categories:
- text-classification
- sentence-similarity
- summarization
language:
- en
tags:
- topic-modeling
- circular-economy
- public-attention
- topic-modeling
- guardian
- reddit
- twitter
- x
- news
- environment
- text-mining
- NLP
pretty_name: Public Attention Text Dataset on Circular Economy for Topic Modelling
size_categories:
- 10K<n<100K
---
### Public Attention Text Dataset on Circular Economy for Topic Modelling
<p align="left">
<a href="https://www.sciencedirect.com/science/article/pii/S2666546824000995"><img src="https://img.shields.io/badge/Journal-Energy%20and%20AI-orange.svg?logo=elsevier" alt="Journal"></a>
<a href="https://arxiv.org/abs/2405.10452"><img src="https://img.shields.io/badge/arXiv-2405.10452-b31b1b.svg?logo=arxiv" alt="arXiv"></a>
<a href="https://doi.org/10.17861/85bf3f9d-dc42-4b5c-8e29-47ddd0f0f687"><img src="https://img.shields.io/badge/dataset-DOI%3A10.17861%2F85bf3f9d--dc42--4b5c--8e29--47ddd0f0f687-blue.svg?logo=dataverse" alt="Dataset DOI"></a>
<a href="https://creativecommons.org/licenses/by-nc/4.0/"><img src="https://img.shields.io/badge/Data%20License-CC%20BY--NC%204.0-lightgrey.svg?logo=creativecommons" alt="CC BY-NC 4.0"></a>
</p>
Our dataset is now publicly available via the university's open access repository:
- **DOI:** [10.17861/85bf3f9d-dc42-4b5c-8e29-47ddd0f0f687](https://doi.org/10.17861/85bf3f9d-dc42-4b5c-8e29-47ddd0f0f687)
- **License:** This dataset is released under the [Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/) license.
**Note:** Please use the DOI link above to access and download the data.
This directory is designated for dataset documentation, metadata, and scripts related to data processing. If you use our dataset, please cite the DOI.
```bibtex
@dataset{song2025public,
author = {Song, Junhao and Yuan, Yingfang and Chang, Kaiwen and Xu, Bing and Xuan, Jin and Pang, Wei},
title = {Public Attention Text Dataset on Circular Economy for Topic Modelling},
year = {2025},
publisher = {Heriot-Watt University},
doi = {10.17861/85bf3f9d-dc42-4b5c-8e29-47ddd0f0f687},
url = {https://doi.org/10.17861/85bf3f9d-dc42-4b5c-8e29-47ddd0f0f687},
note = {EAI2024Data(.zip)}
}
```
---
It is imperative to ensure that any data shared here complies with ethical guidelines and legal standards to protect personal and sensitive information. |