---
license: mit
task_categories:
  - text-classification
language:
  - en
tags:
  - hate-speech
  - classification
  - nlp
  - social-media
pretty_name: New Hatespeech America
configs:
  - config_name: default
    data_files:
      - split: train
        path: hatespeech.csv
dataset_info:
  features:
    - name: text
      dtype: string
    - name: label
      dtype: string
---

# Dataset Card for New Hatespeech America

This dataset contains English social media text data designed for text classification and hate speech detection tasks in Natural Language Processing (NLP).

## Dataset Details

### Dataset Description

The *New Hatespeech America* dataset is curated for researching and detecting hate speech in text. It consists of annotated sentences/posts aimed at training machine learning models to identify toxic, offensive, or hate-speech content.

- **Curated by:** Antontrokez
- **Language(s) (NLP):** English (`en`)
- **License:** MIT
- **Primary Task:** Text Classification / Hate Speech Detection

### Dataset Sources

- **Repository:** Antontrokez/new_hatespeech_america

## Uses

### Direct Use

This dataset can be directly used for:
- Training and benchmarking text classification algorithms.
- Fine-tuning Transformer models (e.g., BERT, RoBERTa) for hate speech detection.
- Academic research on content moderation and social media toxicity analysis.

### Out-of-Scope Use

- Not recommended for deployment in automatic moderation systems without context verification and human oversight.
- Not intended to promote or spread hate speech.

### Data Sources & Collection
The data was collected from various social media platforms, including **Instagram, Threads, Mastodon, Bluesky, Twitter/X, Reddit, 9GAG**, and others, covering the period from **March 2024 to January 2026**. The dataset has been modified and preprocessed specifically for research purposes.

## How to Use

### Using Hugging Face datasets

```python
from datasets import load_dataset

dataset = load_dataset("Antontrokez/new_hatespeech_america")
print(dataset["train"][0])