Sentiment Analysis of ChatGPT Tweets Using Transformer Algorithms

Winardi; Sugeng; Diqi; Mohammad; Sulistyowati; Arum Kurnia; Imlabla; Jelina

Jurnal Informatika dan Rekayasa Perangkat Lunak

Universitas Wahid Hasyim

📄 Abstract

This study explores the application of the Transformer model in sentiment analysis of tweets generated by ChatGPT. We used a Kaggle dataset consisting of 217,623 instances labeled as "Good", "Bad", and "Neutral". The Transformer model demonstrated high accuracy (90%) in classifying sentiments, particularly predicting "Bad" tweets. However, it showed slightly lower performance for the "Good" and "Neutral" categories, indicating areas for future research and model refinement. Our findings contribute to the growing body of evidence supporting deep learning methods in sentiment analysis and underscore the potential of AI models like Transformers in handling complex natural language processing tasks. This study broadens the scope for AI applications in social media sentiment analysis.

🔖 Keywords

#Sentiment Analysis; Transformer Model; ChatGPT; Deep Learning; Social Media Analysis

ℹ️ Informasi Publikasi

Tanggal Publikasi

09 October 2023

Volume / Nomor / Tahun

Volume 5, Nomor 2, Tahun 2023

📝 HOW TO CITE

Winardi, Sugeng; Diqi, Mohammad; Sulistyowati, Arum Kurnia; Imlabla, Jelina, "Sentiment Analysis of ChatGPT Tweets Using Transformer Algorithms," Jurnal Informatika dan Rekayasa Perangkat Lunak, vol. 5, no. 2, Oct. 2023.

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