39 datasets found

A dataset of Hinglish text for code-mixed social media text for hate speech detection

A dataset for hate speech detection on Twitter using a Convolution-GRU based deep neural network.

The MMHS150K dataset consists of 150K multi-modal (images + text) tweets spanning over four hate-inclined topics – racism, sexism, homophobia, and religious extrem-ism.

A review of studies on the detection of racist and sexist hate speech.

A dataset of 16,000 tweets, of which 3,383 tweets were sexist.

The dataset used for hate speech detection on Twitter

The dataset used for hate speech detection on Twitter

The dataset used for hate speech detection on Twitter

The dataset used for hate speech detection on Twitter

The FHM dataset, a multimodal framework for detecting hateful memes on social media.

The FRENK Dataset is a collection of Slovene and English comments annotated for hate speech.

The Wikipedia Hate Speech Dataset is a collection of user comments annotated for hate speech.

The Reddit Hate Detection Dataset is a collection of Reddit comments annotated for hate speech.

The Gab Hate Corpus is a collection of 27k posts annotated for hate speech.

The PEACE dataset is a collection of social media posts and comments annotated for hate speech.

The MUTE dataset is a multimodal dataset for detecting hateful memes.

Automated hate speech detection and the problem of offensive language.

Tweet-BLM: A Hate Speech Dataset and Analysis of Black Lives Matter-related Microblogs on Twitter.

Hate speech detection has become a hot topic in recent years due to the exponential growth of offensive language in social media.

The Dynamic dataset, a collection of tweets generated using a human-and-model-in-the-loop process, containing challenging perturbations.