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Paper Number

1222

Paper Type

Short

Description

Social media sentiment is proven to be an important feature in financial forecasting. While the effect of sentiment is complex and time-varying for traditional financial assets, its role in cryptocurrency markets is unclear. This research explores the predictive power of public sentiment on Bitcoin trading volume. We develop a novel sentiment analysis pipeline for processing Bitcoin-related tweets and achieve state-of-the-art accuracy on a benchmark dataset. Our pipeline also leverages information gain theory to incorporate the impact of textual and non-textual features. We use such features to discern a non-linear relationship between public sentiment and Bitcoin trading volume and discover the optimal predictive horizon for Bitcoin. This research provides a useful module and a foundation for future studies and understanding of Bitcoin market dynamics, and its interaction with social media buzzing.

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07-Blockchain

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COinS
 
Dec 12th, 12:00 AM

Does Social Media Sentiment Predict Bitcoin Trading Volume?

Social media sentiment is proven to be an important feature in financial forecasting. While the effect of sentiment is complex and time-varying for traditional financial assets, its role in cryptocurrency markets is unclear. This research explores the predictive power of public sentiment on Bitcoin trading volume. We develop a novel sentiment analysis pipeline for processing Bitcoin-related tweets and achieve state-of-the-art accuracy on a benchmark dataset. Our pipeline also leverages information gain theory to incorporate the impact of textual and non-textual features. We use such features to discern a non-linear relationship between public sentiment and Bitcoin trading volume and discover the optimal predictive horizon for Bitcoin. This research provides a useful module and a foundation for future studies and understanding of Bitcoin market dynamics, and its interaction with social media buzzing.

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