🐦 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.

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🗂️ 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

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🧩 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

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📊 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

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📈 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%

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🧪 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%

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🧭 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%

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💡 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])

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🏷️ 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}
}

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📬 Contact

For questions, improvements, or collaboration:
Author: Md Abdullah Al Mamun
📧 Email: [email protected]
🌐 Website: TechNTuts