# Is ChatGPT a Good Sentiment Analyzer? A Preliminary Study

**Authors:** Zengzhi Wang, Qiming Xie, Yi Feng, Zixiang Ding, Zinong Yang, Rui Xia  
**arXiv:** [2304.04339](https://arxiv.org/abs/2304.04339)  
**Date:** 2023-04-10  
**Summary page:** https://www.summarizepaper.com/en/paper/2304.04339v2/

## Key points

- Research paper titled "Is ChatGPT a Good Sentiment Analyzer? A Preliminary Study" evaluates ChatGPT as a potential universal sentiment analyzer.
- Three evaluation settings: standard evaluation, polarity shift evaluation, and open-domain evaluation.
- Comparison of ChatGPT with fine-tuned BERT and other state-of-the-art models across 7 sentiment analysis tasks on 17 benchmark datasets.
- Use of popular prompting techniques to enhance ChatGPT's capabilities.
- Human evaluation and qualitative case studies conducted for deeper insight into sentiment analysis abilities of ChatGPT.
- Additional evaluation results include comparative opinion mining and self-consistency assessments.
- Study contributes valuable insights into the effectiveness of ChatGPT in sentiment analysis across diverse contexts and datasets.

## Summary

The research paper titled "Is ChatGPT a Good Sentiment Analyzer? A Preliminary Study" by Zengzhi Wang, Qiming Xie, Yi Feng, Zixiang Ding, Zinong Yang, and Rui Xia delves into the evaluation of ChatGPT as a potential universal sentiment analyzer. With the increasing attention garnered by ChatGPT in both academic circles and the general public, the authors aim to assess its capabilities in understanding opinions, sentiments, and emotions within text. The study encompasses three distinct evaluation settings: standard evaluation, polarity shift evaluation, and open-domain evaluation. Through a comprehensive analysis involving 7 representative sentiment analysis tasks across 17 benchmark datasets, the researchers compare ChatGPT with fine-tuned BERT and other state-of-the-art models. Additionally, various popular prompting techniques are employed to enhance ChatGPT's ability further. Human evaluation is conducted alongside qualitative case studies to gain a profound insight into the sentiment analysis capabilities of ChatGPT. The technical report spans 21 pages and includes additional evaluation results such as comparative opinion mining and self-consistency assessments. These findings provide valuable insights into the potential of ChatGPT as a sentiment analyzer through rigorous evaluations and comparisons with established models in the field. This preliminary study contributes to understanding ChatGPT's effectiveness in analyzing sentiments across diverse contexts and datasets.