Is Chatgpt A Good Sentiment Analyzer? A Preliminary Study

Zengzhi Wang, Qiming Xie, Yi Feng, Zixiang Ding, Zinong Yang, Rui Xia. Arxiv 2023

[Paper]    
Attention Mechanism BERT GPT Model Architecture Prompting Reinforcement Learning

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 opinions, sentiments, and emotions contained in the text. Specifically, we evaluate it in three settings, including standard evaluation, polarity shift evaluation and 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.

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