Update readme file

README.md

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 pretty_name: twitter-sentiment-analysis
 size_categories:
 - 10M<n<100M
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+---
+
+
+# 🐦 Twitter Sentiment Analysis (bdstar/twitter-sentiment-analysis)
+
+🔗 **Dataset Link:** [Hugging Face – bdstar/twitter-sentiment-analysis](https://huggingface.co/datasets/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](https://www.kaggle.com/datasets/prkhrawsthi/twitter-sentiment-dataset-3-million-labelled-rows) |
+| **Test** | Sentiment140 Dataset | 1,600,001 | 198 MB | [Kaggle Dataset](https://www.kaggle.com/datasets/kazanova/sentiment140) |
+| **Validation** | MTEB Tweet Sentiment Extraction | 31,015 | 3.45 MB | [Hugging Face Dataset](https://huggingface.co/datasets/mteb/tweet_sentiment_extraction) |
+
+---
+
+## 🧩 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)](https://www.kaggle.com/datasets/prkhrawsthi/twitter-sentiment-dataset-3-million-labelled-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](https://www.kaggle.com/datasets/kazanova/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](https://huggingface.co/datasets/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)
+
+```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
+@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](https://techntuts.com/)