Is ChatGPT a Good Sentiment Analyzer? A Preliminary Study
Abstract
Recently, ChatGPT has drawn great attention from both the research community and the public. We are particularly interested in whether it can serve as a universal sentiment analyzer. To this end, in this work, we provide a preliminary evaluation of ChatGPT on the understanding of \emph{opinions}, \emph{sentiments}, and \emph{emotions} contained in the text. Specifically, we evaluate it in three settings, including \emph{standard} evaluation, \emph{polarity shift} evaluation and \emph{open-domain} evaluation. We conduct an evaluation on 7 representative sentiment analysis tasks covering 17 benchmark datasets and compare ChatGPT with fine-tuned BERT and corresponding state-of-the-art (SOTA) models on them. We also attempt several popular prompting techniques to elicit the ability further. Moreover, we conduct human evaluation and present some qualitative case studies to gain a deep comprehension of its sentiment analysis capabilities.
Keywords
Cite
@article{arxiv.2304.04339,
title = {Is ChatGPT a Good Sentiment Analyzer? A Preliminary Study},
author = {Zengzhi Wang and Qiming Xie and Yi Feng and Zixiang Ding and Zinong Yang and Rui Xia},
journal= {arXiv preprint arXiv:2304.04339},
year = {2024}
}
Comments
Technical Report; 21 pages, add more evaluation results (e.g., comparative opinion mining, cot, and self-consistency)