license: apache-2.0
task_categories:
- text-classification
- token-classification
language:
- en
tags:
- twitter
- sentiment
- social
- multi-class
pretty_name: twitter-sentiment-analysis
size_categories:
- 10M<n<100M
🐦 Twitter Sentiment Analysis (bdstar/twitter-sentiment-analysis)
🧠 Overview
A refined and merged version of Twitter 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 Twitter Sentiment Analysis and other social media text classification tasks.
🗂️ Dataset Splits
| Split | Source Dataset | Rows | File Size | Link |
|---|---|---|---|---|
| Train | Twitter Sentiment Dataset (3M labeled rows) | 3,142,209 | 361 MB | Kaggle Dataset |
| Test | Sentiment140 Dataset | 1,600,001 | 198 MB | Kaggle Dataset |
| Validation | MTEB Tweet Sentiment Extraction | 31,015 | 3.45 MB | Hugging Face Dataset |
🧩 Column Descriptions
| Column | Type | Description |
|---|---|---|
| ID | Integer | Auto-incremental unique ID for each row |
| text | String | Tweet text content |
| label | String | Sentiment category — one of positive, negative, or neutral |
📊 Dataset Summary
| Property | Value |
|---|---|
| Total Rows | 4,773,225 |
| Columns | 3 |
| File Formats | JSON / Parquet / Pandas / Polars / Croissant |
| License | MIT |
| Author | Md Abdullah Al Mamun |
| Year | 2025 |
| Source | Refined version of Twitter Sentiment Dataset |
📈 Detailed Statistics
🏋️♂️ Train Set
Source: Twitter Sentiment Dataset (3M labeled rows)
File Size: 361 MB
Rows: 3,142,209
| Label | Count | Percentage |
|---|---|---|
| Positive | 1,571,104 | 50.0% |
| Negative | 1,571,105 | 50.0% |
🧪 Test Set
Source: Sentiment140
File Size: 198 MB
Rows: 1,600,001
| Label | Count | Percentage |
|---|---|---|
| Positive | 800,000 | 50.0% |
| Negative | 800,001 | 50.0% |
🧭 Validation Set
Source: MTEB – Tweet Sentiment Extraction
File Size: 3.45 MB
Rows: 31,015
| Label | Count | Percentage |
|---|---|---|
| Neutral | 12,561 | 40.5% |
| Positive | 9,676 | 31.2% |
| Negative | 8,778 | 28.3% |
💡 Usage Example (Python)
from datasets import load_dataset
# Load dataset from Hugging Face
dataset = load_dataset("bdstar/twitter-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:
@dataset{bdstar2025twitter,
title = {Twitter Sentiment Analysis (Refined Dataset)},
author = {Md Abdullah Al Mamun},
year = {2025},
howpublished = {Hugging Face},
url = {https://huggingface.co/datasets/bdstar/twitter-sentiment-analysis}
}
📬 Contact
For questions, improvements, or collaboration:
Author: Md Abdullah Al Mamun
📧 Email: mamunbd.ruet@gmail.com
🌐 Website: TechNTuts