
# Dataset Card for HateOffensive

## 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** : https://arxiv.org/abs/1905.12516 
- **Repository** : https://github.com/t-davidson/hate-speech-and-offensive-language
- **Paper** : https://arxiv.org/abs/1905.12516 
- **Leaderboard** : 
- **Point of Contact** : trd54 at cornell dot edu

### Dataset Summary

### Supported Tasks and Leaderboards
[More Information Needed]

### Languages
English (`en`)

## Dataset Structure

### Data Instances
```
{
"count": 3,
 "hate_speech_annotation": 0,
 "offensive_language_annotation": 0,
 "neither_annotation": 3,
 "label": 2,  # "neither"
 "tweet": "!!! RT @mayasolovely: As a woman you shouldn't complain about cleaning up your house. &amp; as a man you should always take the trash out...")
}
```

### Data Fields

count: (Integer) number of users who coded each tweet (min is 3, sometimes more users coded a tweet when judgments were determined to be unreliable,
hate_speech_annotation: (Integer) number of users who judged the tweet to be hate speech,
offensive_language_annotation: (Integer) number of users who judged the tweet to be offensive,
neither_annotation: (Integer) number of users who judged the tweet to be neither offensive nor non-offensive,
label: (Class Label) integer class label for majority of CF users (0: 'hate-speech', 1: 'offensive-language' or 2: 'neither'),
tweet: (string)

### Data Splits
This dataset is not splitted, only the train split is available.

## Dataset Creation

### Curation Rationale
[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information
Usernames are not anonymized in the dataset.

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information
MIT License

### Citation Information
@inproceedings{hateoffensive,
  title = {Automated Hate Speech Detection and the Problem of Offensive Language},
  author = {Davidson, Thomas and Warmsley, Dana and Macy, Michael and Weber, Ingmar}, 
  booktitle = {Proceedings of the 11th International AAAI Conference on Web and Social Media},
  series = {ICWSM '17},
  year = {2017},
  location = {Montreal, Canada},
  pages = {512-515}
  }

### Contributions

Thanks to [@MisbahKhan789](https://github.com/MisbahKhan789) for adding this dataset.
task_categories:text-classification task_ids:multi-class-classification annotations_creators:crowdsourced language_creators:machine-generated multilinguality:monolingual size_categories:10K<n<100K source_datasets:original language:en license:mit hate-speech-detection arxiv:1905.12516 region:us
{"annotations_creators": ["crowdsourced"], "language_creators": ["machine-generated"], "language": ["en"], "license": ["mit"], "multilinguality": ["monolingual"], "size_categories": ["10K<n<100K"], "source_datasets": ["original"], "task_categories": ["text-classification"], "task_ids": ["multi-class-classification"], "paperswithcode_id": "hate-speech-and-offensive-language", "pretty_name": "HateOffensive", "tags": ["hate-speech-detection"], "dataset_info": {"features": [{"name": "total_annotation_count", "dtype": "int32"}, {"name": "hate_speech_annotations", "dtype": "int32"}, {"name": "offensive_language_annotations", "dtype": "int32"}, {"name": "neither_annotations", "dtype": "int32"}, {"name": "label", "dtype": {"class_label": {"names": {"0": "hate-speech", "1": "offensive-language", "2": "neither"}}}}, {"name": "tweet", "dtype": "string"}], "splits": [{"name": "train", "num_bytes": 2811298, "num_examples": 24783}], "download_size": 2546446, "dataset_size": 2811298}}
TAGS
#task_categories-text-classification #task_ids-multi-class-classification #annotations_creators-crowdsourced #language_creators-machine-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-mit #hate-speech-detection #arxiv-1905.12516 #region-us 


# Dataset Card for HateOffensive

## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions

## Dataset Description
- Homepage : URL 
- Repository : URL
- Paper : URL 
- Leaderboard : 
- Point of Contact : trd54 at cornell dot edu

### Dataset Summary

### Supported Tasks and Leaderboards


### Languages
English ('en')

## Dataset Structure

### Data Instances


### Data Fields

count: (Integer) number of users who coded each tweet (min is 3, sometimes more users coded a tweet when judgments were determined to be unreliable,
hate_speech_annotation: (Integer) number of users who judged the tweet to be hate speech,
offensive_language_annotation: (Integer) number of users who judged the tweet to be offensive,
neither_annotation: (Integer) number of users who judged the tweet to be neither offensive nor non-offensive,
label: (Class Label) integer class label for majority of CF users (0: 'hate-speech', 1: 'offensive-language' or 2: 'neither'),
tweet: (string)

### Data Splits
This dataset is not splitted, only the train split is available.

## Dataset Creation

### Curation Rationale


### Source Data

#### Initial Data Collection and Normalization



#### Who are the source language producers?



### Annotations

#### Annotation process



#### Who are the annotators?



### Personal and Sensitive Information
Usernames are not anonymized in the dataset.

## Considerations for Using the Data

### Social Impact of Dataset



### Discussion of Biases



### Other Known Limitations



## Additional Information

### Dataset Curators



### Licensing Information
MIT License


@inproceedings{hateoffensive,
  title = {Automated Hate Speech Detection and the Problem of Offensive Language},
  author = {Davidson, Thomas and Warmsley, Dana and Macy, Michael and Weber, Ingmar}, 
  booktitle = {Proceedings of the 11th International AAAI Conference on Web and Social Media},
  series = {ICWSM '17},
  year = {2017},
  location = {Montreal, Canada},
  pages = {512-515}
  }

### Contributions

Thanks to @MisbahKhan789 for adding this dataset.
# Dataset Card for HateOffensive ## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions ## Dataset Description
- Homepage : URL 
- Repository : URL
- Paper : URL 
- Leaderboard : 
- Point of Contact : trd54 at cornell dot edu ### Dataset Summary ### Supported Tasks and Leaderboards ### Languages
English ('en') ## Dataset Structure ### Data Instances ### Data Fields

count: (Integer) number of users who coded each tweet (min is 3, sometimes more users coded a tweet when judgments were determined to be unreliable,
hate_speech_annotation: (Integer) number of users who judged the tweet to be hate speech,
offensive_language_annotation: (Integer) number of users who judged the tweet to be offensive,
neither_annotation: (Integer) number of users who judged the tweet to be neither offensive nor non-offensive,
label: (Class Label) integer class label for majority of CF users (0: 'hate-speech', 1: 'offensive-language' or 2: 'neither'),
tweet: (string) ### Data Splits
This dataset is not splitted, only the train split is available. ## Dataset Creation ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information
Usernames are not anonymized in the dataset. ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information
MIT License


@inproceedings{hateoffensive,
  title = {Automated Hate Speech Detection and the Problem of Offensive Language},
  author = {Davidson, Thomas and Warmsley, Dana and Macy, Michael and Weber, Ingmar}, 
  booktitle = {Proceedings of the 11th International AAAI Conference on Web and Social Media},
  series = {ICWSM '17},
  year = {2017},
  location = {Montreal, Canada},
  pages = {512-515}
  } ### Contributions

Thanks to @MisbahKhan789 for adding this dataset.
TAGS
#task_categories-text-classification #task_ids-multi-class-classification #annotations_creators-crowdsourced #language_creators-machine-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-mit #hate-speech-detection #arxiv-1905.12516 #region-us 
 # Dataset Card for HateOffensive ## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions ## Dataset Description
- Homepage : URL 
- Repository : URL
- Paper : URL 
- Leaderboard : 
- Point of Contact : trd54 at cornell dot edu ### Dataset Summary ### Supported Tasks and Leaderboards ### Languages
English ('en') ## Dataset Structure ### Data Instances ### Data Fields

count: (Integer) number of users who coded each tweet (min is 3, sometimes more users coded a tweet when judgments were determined to be unreliable,
hate_speech_annotation: (Integer) number of users who judged the tweet to be hate speech,
offensive_language_annotation: (Integer) number of users who judged the tweet to be offensive,
neither_annotation: (Integer) number of users who judged the tweet to be neither offensive nor non-offensive,
label: (Class Label) integer class label for majority of CF users (0: 'hate-speech', 1: 'offensive-language' or 2: 'neither'),
tweet: (string) ### Data Splits
This dataset is not splitted, only the train split is available. ## Dataset Creation ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information
Usernames are not anonymized in the dataset. ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information
MIT License


@inproceedings{hateoffensive,
  title = {Automated Hate Speech Detection and the Problem of Offensive Language},
  author = {Davidson, Thomas and Warmsley, Dana and Macy, Michael and Weber, Ingmar}, 
  booktitle = {Proceedings of the 11th International AAAI Conference on Web and Social Media},
  series = {ICWSM '17},
  year = {2017},
  location = {Montreal, Canada},
  pages = {512-515}
  } ### Contributions

Thanks to @MisbahKhan789 for adding this dataset.
passage: TAGS
#task_categories-text-classification #task_ids-multi-class-classification #annotations_creators-crowdsourced #language_creators-machine-generated #multilinguality-monolingual #size_categories-10K<n<100K #source_datasets-original #language-English #license-mit #hate-speech-detection #arxiv-1905.12516 #region-us 
# Dataset Card for HateOffensive## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions## Dataset Description
- Homepage : URL 
- Repository : URL
- Paper : URL 
- Leaderboard : 
- Point of Contact : trd54 at cornell dot edu### Dataset Summary### Supported Tasks and Leaderboards### Languages
English ('en')## Dataset Structure### Data Instances### Data Fields

count: (Integer) number of users who coded each tweet (min is 3, sometimes more users coded a tweet when judgments were determined to be unreliable,
hate_speech_annotation: (Integer) number of users who judged the tweet to be hate speech,
offensive_language_annotation: (Integer) number of users who judged the tweet to be offensive,
neither_annotation: (Integer) number of users who judged the tweet to be neither offensive nor non-offensive,
label: (Class Label) integer class label for majority of CF users (0: 'hate-speech', 1: 'offensive-language' or 2: 'neither'),
tweet: (string)### Data Splits
This dataset is not splitted, only the train split is available.