KidzRizal/twitter-sentiment-analysis

Twitter Sentiment Analysis: Prabowo's First 100 Days

Dataset Overview

This dataset contains tweets related to President Prabowo Subianto's first 100 days in office in Indonesia (2024-2029). The tweets have been preprocessed and classified into three sentiment categories using a fine-tuned BERT model for Indonesian language (IndoBERT).

Dataset Details

• Language: Indonesian
• Source: Twitter/X
• Time period: First 100 days of President Prabowo's administration
• Number of samples: 10038 tweets
• Format: CSV

Sentiment Labels:

• Negative (0): Expresses negative sentiment toward the government's performance (3138 tweets, 31.3%)
• Neutral (1): Expresses neutral or factual comments without clear positive or negative sentiment (3278 tweets, 32.7%)
• Positive (2): Expresses positive sentiment or approval of the government's performance (3622 tweets, 36.1%)

Dataset Structure

The dataset has the following columns:

• original_text: The original tweet text
• final_text: The preprocessed tweet text used for classification
• sentiment: The sentiment class (0: negative, 1: neutral, 2: positive)
• sentiment_label: Text representation of the sentiment (negative, neutral, positive)

Usage

from datasets import load_dataset

# Load the dataset
dataset = load_dataset("KidzRizal/twitter-sentiment-analysis")

# Access the first example
print(dataset["train"][0])

# Get dataset information
print(dataset)

Citation

If you use this dataset in your research, please cite:

@misc{twitter_prabowo_sentiment,
  title={Twitter Sentiment Analysis of Prabowo's First 100 Days},
  author={Rizal Wicaksono, Muhammad},
  year={2025},
  howpublished={Hugging Face Datasets},
  url={https://huggingface.co/datasets/KidzRizal/twitter-sentiment-analysis}
}

Acknowledgements

This dataset was created as part of a thesis project at Bina Nusantara University, Indonesia.

License

CC BY-NC-SA 4.0