Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
multi-class-classification
Languages:
English
Size:
100K - 1M
Tags:
emotion-classification
License:
Update files from the datasets library (from 1.3.0)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.3.0
README.md
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---
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---
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# Dataset Card for "emotion"
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## Table of Contents
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Supported Tasks](#supported-tasks)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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- [Data Instances](#data-instances)
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- [Data Fields](#data-fields)
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- [Data Splits Sample Size](#data-splits-sample-size)
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- [Dataset Creation](#dataset-creation)
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- [Curation Rationale](#curation-rationale)
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- [Source Data](#source-data)
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- [Annotations](#annotations)
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- [Personal and Sensitive Information](#personal-and-sensitive-information)
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- [Considerations for Using the Data](#considerations-for-using-the-data)
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- [Social Impact of Dataset](#social-impact-of-dataset)
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- [Discussion of Biases](#discussion-of-biases)
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- [Other Known Limitations](#other-known-limitations)
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- [Additional Information](#additional-information)
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- [Dataset Curators](#dataset-curators)
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- [Licensing Information](#licensing-information)
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- [Citation Information](#citation-information)
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- [Contributions](#contributions)
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## [Dataset Description](#dataset-description)
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- **Homepage:** [https://github.com/dair-ai/emotion_dataset](https://github.com/dair-ai/emotion_dataset)
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- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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- **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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- **Size of downloaded dataset files:** 3.95 MB
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- **Size of the generated dataset:** 4.16 MB
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- **Total amount of disk used:** 8.11 MB
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### [Dataset Summary](#dataset-summary)
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Emotion is a dataset of English Twitter messages with six basic emotions: anger, fear, joy, love, sadness, and surprise. For more detailed information please refer to the paper.
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### [Supported Tasks](#supported-tasks)
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### [Languages](#languages)
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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## [Dataset Structure](#dataset-structure)
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We show detailed information for up to 5 configurations of the dataset.
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### [Data Instances](#data-instances)
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#### default
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- **Size of downloaded dataset files:** 1.97 MB
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- **Size of the generated dataset:** 2.07 MB
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- **Total amount of disk used:** 4.05 MB
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An example of 'train' looks as follows.
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```
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{
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"label": 0,
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"text": "im feeling quite sad and sorry for myself but ill snap out of it soon"
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}
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```
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#### emotion
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- **Size of downloaded dataset files:** 1.97 MB
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- **Size of the generated dataset:** 2.09 MB
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- **Total amount of disk used:** 4.06 MB
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An example of 'validation' looks as follows.
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```
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```
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### [Data Fields](#data-fields)
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The data fields are the same among all splits.
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#### default
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- `text`: a `string` feature.
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- `label`: a classification label, with possible values including `sadness` (0), `joy` (1), `love` (2), `anger` (3), `fear` (4).
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#### emotion
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- `text`: a `string` feature.
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- `label`: a `string` feature.
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### [Data Splits Sample Size](#data-splits-sample-size)
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| name |train|validation|test|
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|-------|----:|---------:|---:|
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|default|16000| 2000|2000|
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|emotion|16000| 2000|2000|
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## [Dataset Creation](#dataset-creation)
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### [Curation Rationale](#curation-rationale)
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### [Source Data](#source-data)
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### [Annotations](#annotations)
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### [Personal and Sensitive Information](#personal-and-sensitive-information)
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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## [Considerations for Using the Data](#considerations-for-using-the-data)
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### [Social Impact of Dataset](#social-impact-of-dataset)
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### [Discussion of Biases](#discussion-of-biases)
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### [Other Known Limitations](#other-known-limitations)
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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## [Additional Information](#additional-information)
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### [Dataset Curators](#dataset-curators)
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### [Licensing Information](#licensing-information)
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[More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
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### [Citation Information](#citation-information)
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```
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@inproceedings{saravia-etal-2018-carer,
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title = "{CARER}: Contextualized Affect Representations for Emotion Recognition",
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author = "Saravia, Elvis and
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Liu, Hsien-Chi Toby and
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Huang, Yen-Hao and
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Wu, Junlin and
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Chen, Yi-Shin",
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booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing",
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month = oct # "-" # nov,
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year = "2018",
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address = "Brussels, Belgium",
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publisher = "Association for Computational Linguistics",
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url = "https://www.aclweb.org/anthology/D18-1404",
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doi = "10.18653/v1/D18-1404",
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pages = "3687--3697",
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abstract = "Emotions are expressed in nuanced ways, which varies by collective or individual experiences, knowledge, and beliefs. Therefore, to understand emotion, as conveyed through text, a robust mechanism capable of capturing and modeling different linguistic nuances and phenomena is needed. We propose a semi-supervised, graph-based algorithm to produce rich structural descriptors which serve as the building blocks for constructing contextualized affect representations from text. The pattern-based representations are further enriched with word embeddings and evaluated through several emotion recognition tasks. Our experimental results demonstrate that the proposed method outperforms state-of-the-art techniques on emotion recognition tasks.",
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}
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```
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### Contributions
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Thanks to [@lhoestq](https://github.com/lhoestq), [@thomwolf](https://github.com/thomwolf), [@lewtun](https://github.com/lewtun) for adding this dataset.
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