Datasets:
Tasks:
Text Classification
Languages:
English
Size:
n<1K
ArXiv:
Tags:
Hate Speech Detection
License:
| annotations_creators: | |
| - crowdsourced | |
| - expert-generated | |
| language_creators: | |
| - found | |
| - other | |
| language: | |
| - en | |
| license: | |
| - agpl-3.0 | |
| multilinguality: | |
| - monolingual | |
| size_categories: | |
| - n<1K | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - text-classification | |
| task_ids: | |
| - multi-label-classification | |
| - sentiment-classification | |
| paperswithcode_id: ethos | |
| pretty_name: onlinE haTe speecH detectiOn dataSet | |
| configs: | |
| - binary | |
| - multilabel | |
| tags: | |
| - Hate Speech Detection | |
| dataset_info: | |
| - config_name: binary | |
| features: | |
| - name: text | |
| dtype: string | |
| - name: label | |
| dtype: | |
| class_label: | |
| names: | |
| '0': no_hate_speech | |
| '1': hate_speech | |
| splits: | |
| - name: train | |
| num_bytes: 124823 | |
| num_examples: 998 | |
| download_size: 123919 | |
| dataset_size: 124823 | |
| - config_name: multilabel | |
| features: | |
| - name: text | |
| dtype: string | |
| - name: violence | |
| dtype: | |
| class_label: | |
| names: | |
| '0': not_violent | |
| '1': violent | |
| - name: directed_vs_generalized | |
| dtype: | |
| class_label: | |
| names: | |
| '0': generalied | |
| '1': directed | |
| - name: gender | |
| dtype: | |
| class_label: | |
| names: | |
| '0': 'false' | |
| '1': 'true' | |
| - name: race | |
| dtype: | |
| class_label: | |
| names: | |
| '0': 'false' | |
| '1': 'true' | |
| - name: national_origin | |
| dtype: | |
| class_label: | |
| names: | |
| '0': 'false' | |
| '1': 'true' | |
| - name: disability | |
| dtype: | |
| class_label: | |
| names: | |
| '0': 'false' | |
| '1': 'true' | |
| - name: religion | |
| dtype: | |
| class_label: | |
| names: | |
| '0': 'false' | |
| '1': 'true' | |
| - name: sexual_orientation | |
| dtype: | |
| class_label: | |
| names: | |
| '0': 'false' | |
| '1': 'true' | |
| splits: | |
| - name: train | |
| num_bytes: 79112 | |
| num_examples: 433 | |
| download_size: 62836 | |
| dataset_size: 79112 | |
| # Dataset Card for Ethos | |
| ## 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:** [ETHOS Hate Speech Dataset](https://github.com/intelligence-csd-auth-gr/Ethos-Hate-Speech-Dataset) | |
| - **Repository:**[ETHOS Hate Speech Dataset](https://github.com/intelligence-csd-auth-gr/Ethos-Hate-Speech-Dataset) | |
| - **Paper:**[ETHOS: an Online Hate Speech Detection Dataset](https://arxiv.org/abs/2006.08328) | |
| ### Dataset Summary | |
| ETHOS: onlinE haTe speecH detectiOn dataSet. This repository contains a dataset for hate speech detection on social media platforms, called Ethos. There are two variations of the dataset: | |
| - **Ethos_Dataset_Binary**: contains 998 comments in the dataset alongside with a label about hate speech *presence* or *absence*. 565 of them do not contain hate speech, while the rest of them, 433, contain. | |
| - **Ethos_Dataset_Multi_Label** which contains 8 labels for the 433 comments with hate speech content. These labels are *violence* (if it incites (1) or not (0) violence), *directed_vs_general* (if it is directed to a person (1) or a group (0)), and 6 labels about the category of hate speech like, *gender*, *race*, *national_origin*, *disability*, *religion* and *sexual_orientation*. | |
| ***Ethos /ˈiːθɒs/*** | |
| is a Greek word meaning “character” that is used to describe the guiding beliefs or ideals that characterize a community, nation, or ideology. The Greeks also used this word to refer to the power of music to influence emotions, behaviors, and even morals. | |
| ### Supported Tasks and Leaderboards | |
| [More Information Needed] | |
| - `text-classification-other-Hate Speech Detection`, `sentiment-classification`,`multi-label-classification`: The dataset can be used to train a model for hate speech detection. Moreover, it can be used as a benchmark dataset for multi label classification algorithms. | |
| ### Languages | |
| The text in the dataset is in English. | |
| ## Dataset Structure | |
| ### Data Instances | |
| A typical data point in the binary version comprises a comment, with a `text` containing the text and a `label` describing if a comment contains hate speech content (1 - hate-speech) or not (0 - non-hate-speech). In the multilabel version more labels like *violence* (if it incites (1) or not (0) violence), *directed_vs_general* (if it is directed to a person (1) or a group (0)), and 6 labels about the category of hate speech like, *gender*, *race*, *national_origin*, *disability*, *religion* and *sexual_orientation* are appearing. | |
| An example from the binary version, which is offensive, but it does not contain hate speech content: | |
| ``` | |
| {'text': 'What the fuck stupid people !!!', | |
| 'label': '0' | |
| } | |
| ``` | |
| An example from the multi-label version, which contains hate speech content towards women (gender): | |
| ``` | |
| {'text': 'You should know women's sports are a joke', | |
| `violence`: 0, | |
| `directed_vs_generalized`: 0, | |
| `gender`: 1, | |
| `race`: 0, | |
| `national_origin`: 0, | |
| `disability`: 0, | |
| `religion`: 0, | |
| `sexual_orientation`: 0 | |
| } | |
| ``` | |
| ### Data Fields | |
| Ethos Binary: | |
| - `text`: a `string` feature containing the text of the comment. | |
| - `label`: a classification label, with possible values including `no_hate_speech`, `hate_speech`. | |
| Ethis Multilabel: | |
| - `text`: a `string` feature containing the text of the comment. | |
| - `violence`: a classification label, with possible values including `not_violent`, `violent`. | |
| - `directed_vs_generalized`: a classification label, with possible values including `generalized`, `directed`. | |
| - `gender`: a classification label, with possible values including `false`, `true`. | |
| - `race`: a classification label, with possible values including `false`, `true`. | |
| - `national_origin`: a classification label, with possible values including `false`, `true`. | |
| - `disability`: a classification label, with possible values including `false`, `true`. | |
| - `religion`: a classification label, with possible values including `false`, `true`. | |
| - `sexual_orientation`: a classification label, with possible values including `false`, `true`. | |
| ### Data Splits | |
| The data is split into binary and multilabel. Multilabel is a subset of the binary version. | |
| | | Instances | Labels | | |
| | ----- | ------ | ----- | | |
| | binary | 998 | 1 | | |
| | multilabel | 433 | 8 | | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| The dataset was build by gathering online comments in Youtube videos and reddit comments, from videos and subreddits which may attract hate speech content. | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| The initial data we used are from the hatebusters platform: [Original data used](https://intelligence.csd.auth.gr/topics/hate-speech-detection/), but they were not included in this dataset | |
| #### Who are the source language producers? | |
| The language producers are users of reddit and Youtube. More informations can be found in this paper: [ETHOS: an Online Hate Speech Detection Dataset](https://arxiv.org/abs/2006.08328) | |
| ### Annotations | |
| #### Annotation process | |
| The annotation process is detailed in the third section of this paper: [ETHOS: an Online Hate Speech Detection Dataset](https://arxiv.org/abs/2006.08328) | |
| #### Who are the annotators? | |
| Originally anotated by Ioannis Mollas and validated through the Figure8 platform (APEN). | |
| ### Personal and Sensitive Information | |
| No personal and sensitive information included in the dataset. | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| This dataset will help on the evolution of the automated hate speech detection tools. Those tools have great impact on preventing social issues. | |
| ### Discussion of Biases | |
| This dataset tries to be unbiased towards its classes and labels. | |
| ### Other Known Limitations | |
| The dataset is relatively small and should be used combined with larger datasets. | |
| ## Additional Information | |
| ### Dataset Curators | |
| The dataset was initially created by [Intelligent Systems Lab](https://intelligence.csd.auth.gr). | |
| ### Licensing Information | |
| The licensing status of the datasets is [GNU GPLv3](https://choosealicense.com/licenses/gpl-3.0/). | |
| ### Citation Information | |
| ``` | |
| @misc{mollas2020ethos, | |
| title={ETHOS: an Online Hate Speech Detection Dataset}, | |
| author={Ioannis Mollas and Zoe Chrysopoulou and Stamatis Karlos and Grigorios Tsoumakas}, | |
| year={2020}, | |
| eprint={2006.08328}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CL} | |
| } | |
| ``` | |
| ### Contributions | |
| Thanks to [@iamollas](https://github.com/iamollas) for adding this dataset. |