Datasets:

tdavidson
/

hate_speech_offensive

	---
	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-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://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](https://github.com/hugoabonizio) for adding this dataset.