FinMoji: A Framework for Emoji-driven Sentiment Analysis in Financial Social Media
This paper explores the use of emojis in financial sentiment analysis, focusing on the social media platform StockTwits. Emojis, increasingly prevalent in digital communication, have potential as compact indicators of investor sentiment, which can be critical for predicting market trends. Our study examines whether emojis alone can serve as reliable proxies for financial sentiment and how they compare with traditional text-based analysis. We conduct a series of experiments using logistic regression and transformer models. We further analyze the performance, computational efficiency, and data requirements of emoji-based versus text-based sentiment classification. Using a balanced dataset o...
| Authors | Ahmed Mahrous, Roberto Di Pietro |
|---|---|
| Primary category | cs.CL |
| Published | 10 May 2026 |
| Last updated at source | 10 May 2026 |
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