abubakaraabi786/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
num_bytes: 3803167
num_examples: 45000
- name: test
num_bytes: 4255901
num_examples: 50000
- name: validation
num_bytes: 396079
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
splits:
- name: train
num_bytes: 338871
num_examples: 3257
- name: test
num_bytes: 146645
num_examples: 1421
- name: validation
num_bytes: 38273
num_examples: 374
download_size: 367016
dataset_size: 523789
- config_name: hate
features:
- name: text
dtype: string
- name: label
dtype:
class_label:
names:
'0': non-hate
'1': hate
splits:
- name: train
num_bytes: 1223650
num_examples: 9000
- name: test
num_bytes: 428934
num_examples: 2970
- name: validation
num_bytes: 154144
num_examples: 1000
download_size: 1196346
dataset_size: 1806728
- config_name: irony
features:
- name: text
dtype: string
- name: label
dtype:
class_label:
names:
'0': non_irony
'1': irony
splits:
- name: train
num_bytes: 259187
num_examples: 2862
- name: test
num_bytes: 75897
num_examples: 784
- name: validation
num_bytes: 86017
num_examples: 955
download_size: 297647
dataset_size: 421101
- config_name: offensive
features:
- name: text
dtype: string
- name: label
dtype:
class_label:
names:
'0': non-offensive
'1': offensive
splits:
- name: train
num_bytes: 1648061
num_examples: 11916
- name: test
num_bytes: 135473
num_examples: 860
- name: validation
num_bytes: 192417
num_examples: 1324
download_size: 1234528
dataset_size: 1975951
- config_name: sentiment
features:
- name: text
dtype: string
- name: label
dtype:
class_label:
names:
'0': negative
'1': neutral
'2': positive
splits:
- name: train
num_bytes: 5425122
num_examples: 45615
- name: test
num_bytes: 1279540
num_examples: 12284
- name: validation
num_bytes: 239084
num_examples: 2000
download_size: 4849675
dataset_size: 6943746
- config_name: stance_abortion
features:
- name: text
dtype: string
- name: label
dtype:
class_label:
names:
'0': none
'1': against
'2': favor
splits:
- name: train
num_bytes: 68694
num_examples: 587
- name: test
num_bytes: 33171
num_examples: 280
- name: validation
num_bytes: 7657
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
splits:
- name: train
num_bytes: 54775
num_examples: 461
- name: test
num_bytes: 25716
num_examples: 220
- name: validation
num_bytes: 6320
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
splits:
- name: train
num_bytes: 40249
num_examples: 355
- name: test
num_bytes: 19925
num_examples: 169
- name: validation
num_bytes: 4801
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:
- name: train
num_bytes: 70509
num_examples: 597
- name: test
num_bytes: 33305
num_examples: 285
- name: validation
num_bytes: 8035
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
num_bytes: 69596
num_examples: 620
- name: test
num_bytes: 34487
num_examples: 295
- name: validation
num_bytes: 7532
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.