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---
license: mit
task_categories:
- text-classification
- token-classification
language:
- en
tags:
- twitter
- tweets
- sentiment
- social
- multi-class
pretty_name: Tweets-Sentiment-Analysis
size_categories:
- 10M<n<100M
---
# 🐦 Tweets-Sentiment-Analysis (bdstar/Tweets-Sentiment-Analysis)
## 🧠 Overview
A **refined and merged version of Tweets text sentiment datasets**, providing a clean and well-balanced dataset for **sentiment classification** across three sentiment categories:
**`positive`**, **`negative`**, and **`neutral`**.
This dataset is split into three parts — **train**, **test**, and **validation** — each sourced from highly reputable open datasets.
It is designed for training, evaluating, and benchmarking **NLP models** for **Tweets Sentiment Analysis** and other **social media text classification** tasks.
---
## 🗂️ Dataset Splits
| # | Split | Name | Negative | Neutral | Positive | % Negative | % Neutral | % Positive | Total |
|---|-------------|-----------------------------------------|----------|---------|----------|------------|-----------|------------|----------|
| 1 | Train | Sentiment140 (positive-sentence) | 71,462 | 233,345 | 483,261 | 9.067999 | 29.609754 | 61.322246 | 788,068 |
| 2 | Train | Sentiment140 (negative-sentence) | 451,341 | 191,650 | 136,801 | 57.879665 | 24.577067 | 17.543268 | 779,792 |
| 3 | Train | DailyDialog | 12,623 | 45,674 | 20,226 | 16.075545 | 58.166397 | 25.758058 | 78,523 |
| 4 | Test | ChatGPT Tweets Sentiment Analysis | 194,425 | 360,060 | 295,108 | 22.884487 | 42.380293 | 34.735220 | 849,593 |
| 5 | Validation | mteb-tweet_sentiment_extraction | 10,083 | 7,969 | 12,070 | 33.473873 | 26.455747 | 40.070380 | 30,122 |
| | **Total** | — | **739,934** | **838,698** | **947,466** | **29.291579** | **33.201325** | **37.507096** | **2,526,098** |
The possiblity value of Negative, Positive and Neutral for a text has been calculated by the model [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest)
---
## 🧩 Column Descriptions
| Column | Type | Description |
|---------|------|-------------|
| **ID** | Integer | Auto-incremental unique ID for each row |
| **text** | String | Tweet text content |
| **negative** | Float | Possiblity the text be a negative |
| **neutral** | Float | Possiblity the text be a neutral |
| **positive** | Float | Possiblity the text be a positive |
| **label** | String | Sentiment category — one of `positive`, `negative`, or `neutral` |
---
## 📊 Dataset Summary
| Property | Value |
|-----------|-------|
| **Total Rows** | 2,526,098 |
| **Columns** | 6 |
| **File Formats** | JSON / Parquet / Pandas / Polars / Croissant |
| **License** | MIT |
| **Author** | Md Abdullah Al Mamun |
| **Year** | 2025 |
| **Source** | Refined version of Tweets Sentiment Dataset |
---
## 💡 Usage Example (Python)
```python
from datasets import load_dataset
# Load dataset from Hugging Face
ds = load_dataset("bdstar/Tweets-Sentiment-Analysis")
# Access splits
train = dataset["train"]
test = dataset["test"]
validation = dataset["validation"]
# Display sample
print(train[0])
```
---
## 🏷️ Citation
If you use this dataset in your research or application, please cite as:
```bibtex
@dataset{bdstar2025Tweets,
title = {Tweets-Sentiment-Analysis},
author = {Md Abdullah Al Mamun},
year = {2025},
howpublished = {Hugging Face},
url = {https://huggingface.co/datasets/bdstar/Tweets-Sentiment-Analysis}
}
```
---
## 📬 Contact
For questions, improvements, or collaboration:
**Author:** Md Abdullah Al Mamun
📧 **Email:** mamunbd.ruet@gmail.com
🌐 **Website:** [TechNTuts](https://techntuts.com/)
💼 **Linkedin:** [WebRock](https://www.linkedin.com/in/webrock/) |