Predicting stock prices with ChatGPT-annotated Reddit sentiment

July 21, 2025 ยท Declared Dead ยท ๐Ÿ› International Conference on Conceptual Structures

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Authors Mateusz Kmak, Kamil Chmurzyล„ski, Kamil Matejuk, Paweล‚ Kotzbach, Jan Kocoล„ arXiv ID 2507.22922 Category cs.CL: Computation & Language Cross-listed cs.AI, cs.SI Citations 1 Venue International Conference on Conceptual Structures Last Checked 5 months ago
Abstract
The surge of retail investor activity on social media, exemplified by the 2021 GameStop short squeeze, raised questions about the influence of online sentiment on stock prices. This paper explores whether sentiment derived from social media discussions can meaningfully predict stock market movements. We focus on Reddit's r/wallstreetbets and analyze sentiment related to two companies: GameStop (GME) and AMC Entertainment (AMC). To assess sentiment's role, we employ two existing text-based sentiment analysis methods and introduce a third, a ChatGPT-annotated and fine-tuned RoBERTa-based model designed to better interpret the informal language and emojis prevalent in social media discussions. We use correlation and causality metrics to determine these models' predictive power. Surprisingly, our findings suggest that social media sentiment has only a weak correlation with stock prices. At the same time, simpler metrics, such as the volume of comments and Google search trends, exhibit stronger predictive signals. These results highlight the complexity of retail investor behavior and suggest that traditional sentiment analysis may not fully capture the nuances of market-moving online discussions.
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