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Social media signals have been successfully used to develop large-scalepredictive and anticipatory analytics. For example, forecasting stock marketprices and influenza outbreaks. Recently, social data has been explored toforecast price fluctuations of cryptocurrencies, which are a novel disruptivetechnology with significant political and economic implications. In this paperwe leverage and contrast the predictive power of social signals, specificallyuser behavior and communication patterns, from multiple social platforms GitHuband Reddit to forecast prices for three cyptocurrencies with high developer andcommunity interest - Bitcoin, Ethereum, and Monero. We evaluate the performanceof neural network models that rely on long short-term memory units (LSTMs)trained on historical price data and social data against price only LSTMs andbaseline autoregressive integrated moving average (ARIMA) models, commonly usedto predict stock prices. Our results not only demonstrate that social signalsreduce error when forecasting daily coin price, but also show that the languageused in comments within the official communities on Reddit (r/Bitcoin,r/Ethereum, and r/Monero) are the best predictors overall. We observe thatmodels are more accurate in forecasting price one day ahead for Bitcoin (4%root mean squared percent error) compared to Ethereum (7%) and Monero (8%).

Improved Forecasting of Cryptocurrency Price using Social Signals