Abstract
This research uses ChatGPT-3.5 and ChatGPT-4 to investigate tone manipulation in the management discussion and analysis of annual reports of Chinese-listed companies. We find that the quantification of emotional content in text using financial BERT model and dictionary approach is inconsistent due to two kinds of manipulation: "Expression Manipulation" and "Word Manipulation". Based on ChatGPT we verify the manipulative behavior of complex expressions and sentiment word substitutions. Our research suggests that using ChatGPT with appropriate cue words can help alleviate tone manipulation in financial texts, with GPT-4 having a better effect.
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