---
license: ecl-2.0
task_categories:
- text-classification
language:
- en
- es
tags:
- public
- text
- education
- sentiment-analysis
pretty_name: TweetFeels 1m4
size_categories:
- 100K<n<1M
---

# TweetFeels 1m4


An 1-million-tweet sentiment corpus harvested from Twitter and annotated with four fine-grained categories: positive, negative, uncertainty, and litigious. Each record carries three clean, tab-separated fields:  

- **Language** – ISO-639 code of the tweet’s detected language  
- **Text** – the full tweet text, preserved with original casing and emojis  
- **Label** – one of {positive, negative, uncertainty, litigious} determined by an automated labelling pipeline  

The dataset covers multiple languages and informal, real-time expressions typical of Twitter, offering a sizeable, ready-to-use resource for multi-class sentiment and legal-tone modelling.

**Acknowledgements**: The dataset is hosted on [Kaggle—Sentiment Dataset with 1 Million Tweets](https://www.kaggle.com/datasets/tariqsays/sentiment-dataset-with-1-million-tweets)