README.md

metadata

annotations_creators:
  - expert-generated
  - crowdsourced
language_creators:
  - found
language:
  - en
license:
  - unknown
multilinguality:
  - monolingual
size_categories:
  - 10K<n<100K
source_datasets:
  - original
task_categories:
  - text-classification
task_ids: []
paperswithcode_id: hate-speech-and-offensive-language
pretty_name: Hate Speech and Offensive Language
tags:
  - hate-speech-detection
dataset_info:
  features:
    - name: count
      dtype: int64
    - name: hate_speech_count
      dtype: int64
    - name: offensive_language_count
      dtype: int64
    - name: neither_count
      dtype: int64
    - name: class
      dtype:
        class_label:
          names:
            '0': hate speech
            '1': offensive language
            '2': neither
    - name: tweet
      dtype: string
  splits:
    - name: train
      num_bytes: 3207814
      num_examples: 24783
  download_size: 1627672
  dataset_size: 3207814
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
train-eval-index:
  - config: default
    task: text-classification
    task_id: multi_class_classification
    splits:
      train_split: train
    col_mapping:
      tweet: 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 [Dataset Name]

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: https://github.com/t-davidson/hate-speech-and-offensive-language
• Repository: https://github.com/t-davidson/hate-speech-and-offensive-language
• Paper: https://arxiv.org/abs/1703.04009
• Leaderboard:
• Point of Contact: https://docs.google.com/forms/d/e/1FAIpQLSdrPNlfVBlqxun2tivzAtsZaOoPC5YYMocn-xscCgeRakLXHg/viewform?usp=pp_url&entry.1506871634&entry.147453066&entry.1390333885&entry.516829772

Dataset Summary

An annotated dataset for hate speech and offensive language detection on tweets.

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. & 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) 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 @hugoabonizio for adding this dataset.