Datasets:
tweet_eval

	---
	annotations_creators:
	- found
	language_creators:
	- found
	language:
	- en
	license:
	- unknown
	multilinguality:
	- monolingual
	size_categories:
	- 100K<n<1M
	- 10K<n<100K
	- 1K<n<10K
	- n<1K
	source_datasets:
	- extended\|other-tweet-datasets
	task_categories:
	- text-classification
	task_ids:
	- intent-classification
	- multi-class-classification
	- sentiment-classification
	paperswithcode_id: tweeteval
	pretty_name: TweetEval
	config_names:
	- emoji
	- emotion
	- hate
	- irony
	- offensive
	- sentiment
	- stance_abortion
	- stance_atheism
	- stance_climate
	- stance_feminist
	- stance_hillary
	dataset_info:
	- config_name: emoji
	features:
	- name: text
	dtype: string
	- name: label
	dtype:
	class_label:
	names:
	'0': ❤
	'1': 😍
	'2': 😂
	'3': 💕
	'4': 🔥
	'5': 😊
	'6': 😎
	'7': ✨
	'8': 💙
	'9': 😘
	'10': 📷
	'11': 🇺🇸
	'12': ☀
	'13': 💜
	'14': 😉
	'15': 💯
	'16': 😁
	'17': 🎄
	'18': 📸
	'19': 😜
	splits:
	- name: train
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	num_examples: 45000
	- name: test
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	num_examples: 50000
	- name: validation
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	num_examples: 5000
	download_size: 5939308
	dataset_size: 8455147
	- config_name: emotion
	features:
	- name: text
	dtype: string
	- name: label
	dtype:
	class_label:
	names:
	'0': anger
	'1': joy
	'2': optimism
	'3': sadness
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	- name: test
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	- name: validation
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	dataset_size: 523789
	- config_name: hate
	features:
	- name: text
	dtype: string
	- name: label
	dtype:
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	'1': hate
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	num_examples: 2970
	- name: validation
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	num_examples: 1000
	download_size: 1196346
	dataset_size: 1806728
	- config_name: irony
	features:
	- name: text
	dtype: string
	- name: label
	dtype:
	class_label:
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	'0': non_irony
	'1': irony
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	- name: test
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	- name: validation
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	num_examples: 955
	download_size: 297647
	dataset_size: 421101
	- config_name: offensive
	features:
	- name: text
	dtype: string
	- name: label
	dtype:
	class_label:
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	'0': non-offensive
	'1': offensive
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	- name: test
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	- name: validation
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	download_size: 1234528
	dataset_size: 1975951
	- config_name: sentiment
	features:
	- name: text
	dtype: string
	- name: label
	dtype:
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	'0': negative
	'1': neutral
	'2': positive
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	- name: test
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	num_examples: 12284
	- name: validation
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	num_examples: 2000
	download_size: 4849675
	dataset_size: 6943746
	- config_name: stance_abortion
	features:
	- name: text
	dtype: string
	- name: label
	dtype:
	class_label:
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	'0': none
	'1': against
	'2': favor
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	num_examples: 587
	- name: test
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	num_examples: 280
	- name: validation
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	num_examples: 66
	download_size: 73517
	dataset_size: 109522
	- config_name: stance_atheism
	features:
	- name: text
	dtype: string
	- name: label
	dtype:
	class_label:
	names:
	'0': none
	'1': against
	'2': favor
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	- name: test
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	num_examples: 220
	- name: validation
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	num_examples: 52
	download_size: 62265
	dataset_size: 86811
	- config_name: stance_climate
	features:
	- name: text
	dtype: string
	- name: label
	dtype:
	class_label:
	names:
	'0': none
	'1': against
	'2': favor
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	- name: test
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	num_examples: 169
	- name: validation
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	num_examples: 40
	download_size: 48493
	dataset_size: 64975
	- config_name: stance_feminist
	features:
	- name: text
	dtype: string
	- name: label
	dtype:
	class_label:
	names:
	'0': none
	'1': against
	'2': favor
	splits:
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	- name: test
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	num_examples: 285
	- name: validation
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	num_examples: 67
	download_size: 76345
	dataset_size: 111849
	- config_name: stance_hillary
	features:
	- name: text
	dtype: string
	- name: label
	dtype:
	class_label:
	names:
	'0': none
	'1': against
	'2': favor
	splits:
	- name: train
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	num_examples: 620
	- name: test
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	num_examples: 295
	- name: validation
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	num_examples: 69
	download_size: 74057
	dataset_size: 111615
	configs:
	- config_name: emoji
	data_files:
	- split: train
	path: emoji/train-*
	- split: test
	path: emoji/test-*
	- split: validation
	path: emoji/validation-*
	- config_name: emotion
	data_files:
	- split: train
	path: emotion/train-*
	- split: test
	path: emotion/test-*
	- split: validation
	path: emotion/validation-*
	- config_name: hate
	data_files:
	- split: train
	path: hate/train-*
	- split: test
	path: hate/test-*
	- split: validation
	path: hate/validation-*
	- config_name: irony
	data_files:
	- split: train
	path: irony/train-*
	- split: test
	path: irony/test-*
	- split: validation
	path: irony/validation-*
	- config_name: offensive
	data_files:
	- split: train
	path: offensive/train-*
	- split: test
	path: offensive/test-*
	- split: validation
	path: offensive/validation-*
	- config_name: sentiment
	data_files:
	- split: train
	path: sentiment/train-*
	- split: test
	path: sentiment/test-*
	- split: validation
	path: sentiment/validation-*
	- config_name: stance_abortion
	data_files:
	- split: train
	path: stance_abortion/train-*
	- split: test
	path: stance_abortion/test-*
	- split: validation
	path: stance_abortion/validation-*
	- config_name: stance_atheism
	data_files:
	- split: train
	path: stance_atheism/train-*
	- split: test
	path: stance_atheism/test-*
	- split: validation
	path: stance_atheism/validation-*
	- config_name: stance_climate
	data_files:
	- split: train
	path: stance_climate/train-*
	- split: test
	path: stance_climate/test-*
	- split: validation
	path: stance_climate/validation-*
	- config_name: stance_feminist
	data_files:
	- split: train
	path: stance_feminist/train-*
	- split: test
	path: stance_feminist/test-*
	- split: validation
	path: stance_feminist/validation-*
	- config_name: stance_hillary
	data_files:
	- split: train
	path: stance_hillary/train-*
	- split: test
	path: stance_hillary/test-*
	- split: validation
	path: stance_hillary/validation-*
	train-eval-index:
	- config: emotion
	task: text-classification
	task_id: multi_class_classification
	splits:
	train_split: train
	eval_split: test
	col_mapping:
	text: text
	label: target
	metrics:
	- type: accuracy
	name: Accuracy
	- type: f1
	name: F1 macro
	args:
	average: macro
	- type: f1
	name: F1 micro
	args:
	average: micro
	- type: f1
	name: F1 weighted
	args:
	average: weighted
	- type: precision
	name: Precision macro
	args:
	average: macro
	- type: precision
	name: Precision micro
	args:
	average: micro
	- type: precision
	name: Precision weighted
	args:
	average: weighted
	- type: recall
	name: Recall macro
	args:
	average: macro
	- type: recall
	name: Recall micro
	args:
	average: micro
	- type: recall
	name: Recall weighted
	args:
	average: weighted
	- config: hate
	task: text-classification
	task_id: binary_classification
	splits:
	train_split: train
	eval_split: test
	col_mapping:
	text: text
	label: target
	metrics:
	- type: accuracy
	name: Accuracy
	- type: f1
	name: F1 binary
	args:
	average: binary
	- type: precision
	name: Precision macro
	args:
	average: macro
	- type: precision
	name: Precision micro
	args:
	average: micro
	- type: precision
	name: Precision weighted
	args:
	average: weighted
	- type: recall
	name: Recall macro
	args:
	average: macro
	- type: recall
	name: Recall micro
	args:
	average: micro
	- type: recall
	name: Recall weighted
	args:
	average: weighted
	- config: irony
	task: text-classification
	task_id: binary_classification
	splits:
	train_split: train
	eval_split: test
	col_mapping:
	text: text
	label: target
	metrics:
	- type: accuracy
	name: Accuracy
	- type: f1
	name: F1 binary
	args:
	average: binary
	- type: precision
	name: Precision macro
	args:
	average: macro
	- type: precision
	name: Precision micro
	args:
	average: micro
	- type: precision
	name: Precision weighted
	args:
	average: weighted
	- type: recall
	name: Recall macro
	args:
	average: macro
	- type: recall
	name: Recall micro
	args:
	average: micro
	- type: recall
	name: Recall weighted
	args:
	average: weighted
	- config: offensive
	task: text-classification
	task_id: binary_classification
	splits:
	train_split: train
	eval_split: test
	col_mapping:
	text: text
	label: target
	metrics:
	- type: accuracy
	name: Accuracy
	- type: f1
	name: F1 binary
	args:
	average: binary
	- type: precision
	name: Precision macro
	args:
	average: macro
	- type: precision
	name: Precision micro
	args:
	average: micro
	- type: precision
	name: Precision weighted
	args:
	average: weighted
	- type: recall
	name: Recall macro
	args:
	average: macro
	- type: recall
	name: Recall micro
	args:
	average: micro
	- type: recall
	name: Recall weighted
	args:
	average: weighted
	- config: sentiment
	task: text-classification
	task_id: multi_class_classification
	splits:
	train_split: train
	eval_split: test
	col_mapping:
	text: text
	label: target
	metrics:
	- type: accuracy
	name: Accuracy
	- type: f1
	name: F1 macro
	args:
	average: macro
	- type: f1
	name: F1 micro
	args:
	average: micro
	- type: f1
	name: F1 weighted
	args:
	average: weighted
	- type: precision
	name: Precision macro
	args:
	average: macro
	- type: precision
	name: Precision micro
	args:
	average: micro
	- type: precision
	name: Precision weighted
	args:
	average: weighted
	- type: recall
	name: Recall macro
	args:
	average: macro
	- type: recall
	name: Recall micro
	args:
	average: micro
	- type: recall
	name: Recall weighted
	args:
	average: weighted
	---

	# Dataset Card for tweet_eval

	## Table of Contents
	- [Dataset Description](#dataset-description)
	- [Dataset Summary](#dataset-summary)
	- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
	- [Languages](#languages)
	- [Dataset Structure](#dataset-structure)
	- [Data Instances](#data-instances)
	- [Data Fields](#data-fields)
	- [Data Splits](#data-splits)
	- [Dataset Creation](#dataset-creation)
	- [Curation Rationale](#curation-rationale)
	- [Source Data](#source-data)
	- [Annotations](#annotations)
	- [Personal and Sensitive Information](#personal-and-sensitive-information)
	- [Considerations for Using the Data](#considerations-for-using-the-data)
	- [Social Impact of Dataset](#social-impact-of-dataset)
	- [Discussion of Biases](#discussion-of-biases)
	- [Other Known Limitations](#other-known-limitations)
	- [Additional Information](#additional-information)
	- [Dataset Curators](#dataset-curators)
	- [Licensing Information](#licensing-information)
	- [Citation Information](#citation-information)
	- [Contributions](#contributions)

	## Dataset Description

	- Homepage: [Needs More Information]
	- Repository: [GitHub](https://github.com/cardiffnlp/tweeteval)
	- Paper: [EMNLP Paper](https://arxiv.org/pdf/2010.12421.pdf)
	- Leaderboard: [GitHub Leaderboard](https://github.com/cardiffnlp/tweeteval)
	- Point of Contact: [Needs More Information]

	### Dataset Summary

	TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. The tasks include - irony, hate, offensive, stance, emoji, emotion, and sentiment. All tasks have been unified into the same benchmark, with each dataset presented in the same format and with fixed training, validation and test splits.

	### Supported Tasks and Leaderboards

	- `text_classification`: The dataset can be trained using a SentenceClassification model from HuggingFace transformers.

	### Languages

	The text in the dataset is in English, as spoken by Twitter users.

	## Dataset Structure

	### Data Instances

	An instance from `emoji` config:

	```
	{'label': 12, 'text': 'Sunday afternoon walking through Venice in the sun with @user ️ ️ ️ @ Abbot Kinney, Venice'}
	```

	An instance from `emotion` config:

	```
	{'label': 2, 'text': "“Worry is a down payment on a problem you may never have'. \xa0Joyce Meyer. #motivation #leadership #worry"}
	```

	An instance from `hate` config:

	```
	{'label': 0, 'text': '@user nice new signage. Are you not concerned by Beatlemania -style hysterical crowds crongregating on you…'}
	```

	An instance from `irony` config:

	```
	{'label': 1, 'text': 'seeing ppl walking w/ crutches makes me really excited for the next 3 weeks of my life'}
	```

	An instance from `offensive` config:

	```
	{'label': 0, 'text': '@user Bono... who cares. Soon people will understand that they gain nothing from following a phony celebrity. Become a Leader of your people instead or help and support your fellow countrymen.'}
	```

	An instance from `sentiment` config:

	```
	{'label': 2, 'text': '"QT @user In the original draft of the 7th book, Remus Lupin survived the Battle of Hogwarts. #HappyBirthdayRemusLupin"'}
	```

	An instance from `stance_abortion` config:

	```
	{'label': 1, 'text': 'we remind ourselves that love means to be willing to give until it hurts - Mother Teresa'}
	```

	An instance from `stance_atheism` config:

	```
	{'label': 1, 'text': '@user Bless Almighty God, Almighty Holy Spirit and the Messiah. #SemST'}
	```

	An instance from `stance_climate` config:

	```
	{'label': 0, 'text': 'Why Is The Pope Upset? via @user #UnzippedTruth #PopeFrancis #SemST'}
	```

	An instance from `stance_feminist` config:

	```
	{'label': 1, 'text': "@user @user is the UK's answer to @user and @user #GamerGate #SemST"}
	```

	An instance from `stance_hillary` config:

	```
	{'label': 1, 'text': "If a man demanded staff to get him an ice tea he'd be called a sexists elitist pig.. Oink oink #Hillary #SemST"}
	```

	### Data Fields
	For `emoji` config:

	- `text`: a `string` feature containing the tweet.

	- `label`: an `int` classification label with the following mapping:

	`0`: ❤

	`1`: 😍

	`2`: 😂

	`3`: 💕

	`4`: 🔥

	`5`: 😊

	`6`: 😎

	`7`: ✨

	`8`: 💙

	`9`: 😘

	`10`: 📷

	`11`: 🇺🇸

	`12`: ☀

	`13`: 💜

	`14`: 😉

	`15`: 💯

	`16`: 😁

	`17`: 🎄

	`18`: 📸

	`19`: 😜

	For `emotion` config:

	- `text`: a `string` feature containing the tweet.

	- `label`: an `int` classification label with the following mapping:

	`0`: anger

	`1`: joy

	`2`: optimism

	`3`: sadness

	For `hate` config:

	- `text`: a `string` feature containing the tweet.

	- `label`: an `int` classification label with the following mapping:

	`0`: non-hate

	`1`: hate

	For `irony` config:

	- `text`: a `string` feature containing the tweet.

	- `label`: an `int` classification label with the following mapping:

	`0`: non_irony

	`1`: irony

	For `offensive` config:

	- `text`: a `string` feature containing the tweet.

	- `label`: an `int` classification label with the following mapping:

	`0`: non-offensive

	`1`: offensive

	For `sentiment` config:

	- `text`: a `string` feature containing the tweet.

	- `label`: an `int` classification label with the following mapping:

	`0`: negative

	`1`: neutral

	`2`: positive

	For `stance_abortion` config:

	- `text`: a `string` feature containing the tweet.

	- `label`: an `int` classification label with the following mapping:

	`0`: none

	`1`: against

	`2`: favor

	For `stance_atheism` config:

	- `text`: a `string` feature containing the tweet.

	- `label`: an `int` classification label with the following mapping:

	`0`: none

	`1`: against

	`2`: favor

	For `stance_climate` config:

	- `text`: a `string` feature containing the tweet.

	- `label`: an `int` classification label with the following mapping:

	`0`: none

	`1`: against

	`2`: favor

	For `stance_feminist` config:

	- `text`: a `string` feature containing the tweet.

	- `label`: an `int` classification label with the following mapping:

	`0`: none

	`1`: against

	`2`: favor

	For `stance_hillary` config:

	- `text`: a `string` feature containing the tweet.

	- `label`: an `int` classification label with the following mapping:

	`0`: none

	`1`: against

	`2`: favor



	### Data Splits

	\| name \| train \| validation \| test \|
	\| --------------- \| ----- \| ---------- \| ----- \|
	\| emoji \| 45000 \| 5000 \| 50000 \|
	\| emotion \| 3257 \| 374 \| 1421 \|
	\| hate \| 9000 \| 1000 \| 2970 \|
	\| irony \| 2862 \| 955 \| 784 \|
	\| offensive \| 11916 \| 1324 \| 860 \|
	\| sentiment \| 45615 \| 2000 \| 12284 \|
	\| stance_abortion \| 587 \| 66 \| 280 \|
	\| stance_atheism \| 461 \| 52 \| 220 \|
	\| stance_climate \| 355 \| 40 \| 169 \|
	\| stance_feminist \| 597 \| 67 \| 285 \|
	\| stance_hillary \| 620 \| 69 \| 295 \|

	## Dataset Creation

	### Curation Rationale

	[Needs More Information]

	### Source Data

	#### Initial Data Collection and Normalization

	[Needs More Information]

	#### Who are the source language producers?

	[Needs More Information]

	### Annotations

	#### Annotation process

	[Needs More Information]

	#### Who are the annotators?

	[Needs More Information]

	### Personal and Sensitive Information

	[Needs More Information]

	## Considerations for Using the Data

	### Social Impact of Dataset

	[Needs More Information]

	### Discussion of Biases

	[Needs More Information]

	### Other Known Limitations

	[Needs More Information]

	## Additional Information

	### Dataset Curators

	Francesco Barbieri, Jose Camacho-Collados, Luis Espiinosa-Anke and Leonardo Neves through Cardiff NLP.

	### Licensing Information

	This is not a single dataset, therefore each subset has its own license (the collection itself does not have additional restrictions).

	All of the datasets require complying with Twitter [Terms Of Service](https://twitter.com/tos) and Twitter API [Terms Of Service](https://developer.twitter.com/en/developer-terms/agreement-and-policy)

	Additionally the license are:
	- emoji: Undefined
	- emotion(EmoInt): Undefined
	- hate (HateEval): Need permission [here](http://hatespeech.di.unito.it/hateval.html)
	- irony: Undefined
	- Offensive: Undefined
	- Sentiment: [Creative Commons Attribution 3.0 Unported License](https://groups.google.com/g/semevaltweet/c/k5DDcvVb_Vo/m/zEOdECFyBQAJ)
	- Stance: Undefined


	### Citation Information

	```
	@inproceedings{barbieri2020tweeteval,
	title={{TweetEval:Unified Benchmark and Comparative Evaluation for Tweet Classification}},
	author={Barbieri, Francesco and Camacho-Collados, Jose and Espinosa-Anke, Luis and Neves, Leonardo},
	booktitle={Proceedings of Findings of EMNLP},
	year={2020}
	}
	```

	If you use any of the TweetEval datasets, please cite their original publications:

	#### Emotion Recognition:
	```
	@inproceedings{mohammad2018semeval,
	title={Semeval-2018 task 1: Affect in tweets},
	author={Mohammad, Saif and Bravo-Marquez, Felipe and Salameh, Mohammad and Kiritchenko, Svetlana},
	booktitle={Proceedings of the 12th international workshop on semantic evaluation},
	pages={1--17},
	year={2018}
	}

	```
	#### Emoji Prediction:
	```
	@inproceedings{barbieri2018semeval,
	title={Semeval 2018 task 2: Multilingual emoji prediction},
	author={Barbieri, Francesco and Camacho-Collados, Jose and Ronzano, Francesco and Espinosa-Anke, Luis and
	Ballesteros, Miguel and Basile, Valerio and Patti, Viviana and Saggion, Horacio},
	booktitle={Proceedings of The 12th International Workshop on Semantic Evaluation},
	pages={24--33},
	year={2018}
	}
	```

	#### Irony Detection:
	```
	@inproceedings{van2018semeval,
	title={Semeval-2018 task 3: Irony detection in english tweets},
	author={Van Hee, Cynthia and Lefever, Els and Hoste, V{\'e}ronique},
	booktitle={Proceedings of The 12th International Workshop on Semantic Evaluation},
	pages={39--50},
	year={2018}
	}
	```

	#### Hate Speech Detection:
	```
	@inproceedings{basile-etal-2019-semeval,
	title = "{S}em{E}val-2019 Task 5: Multilingual Detection of Hate Speech Against Immigrants and Women in {T}witter",
	author = "Basile, Valerio and Bosco, Cristina and Fersini, Elisabetta and Nozza, Debora and Patti, Viviana and
	Rangel Pardo, Francisco Manuel and Rosso, Paolo and Sanguinetti, Manuela",
	booktitle = "Proceedings of the 13th International Workshop on Semantic Evaluation",
	year = "2019",
	address = "Minneapolis, Minnesota, USA",
	publisher = "Association for Computational Linguistics",
	url = "https://www.aclweb.org/anthology/S19-2007",
	doi = "10.18653/v1/S19-2007",
	pages = "54--63"
	}
	```
	#### Offensive Language Identification:
	```
	@inproceedings{zampieri2019semeval,
	title={SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval)},
	author={Zampieri, Marcos and Malmasi, Shervin and Nakov, Preslav and Rosenthal, Sara and Farra, Noura and Kumar, Ritesh},
	booktitle={Proceedings of the 13th International Workshop on Semantic Evaluation},
	pages={75--86},
	year={2019}
	}
	```

	#### Sentiment Analysis:
	```
	@inproceedings{rosenthal2017semeval,
	title={SemEval-2017 task 4: Sentiment analysis in Twitter},
	author={Rosenthal, Sara and Farra, Noura and Nakov, Preslav},
	booktitle={Proceedings of the 11th international workshop on semantic evaluation (SemEval-2017)},
	pages={502--518},
	year={2017}
	}
	```

	#### Stance Detection:
	```
	@inproceedings{mohammad2016semeval,
	title={Semeval-2016 task 6: Detecting stance in tweets},
	author={Mohammad, Saif and Kiritchenko, Svetlana and Sobhani, Parinaz and Zhu, Xiaodan and Cherry, Colin},
	booktitle={Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)},
	pages={31--41},
	year={2016}
	}
	```

	### Contributions

	Thanks to [@gchhablani](https://github.com/gchhablani) and [@abhishekkrthakur](https://github.com/abhishekkrthakur) for adding this dataset.