Cryptocurrency ecosystems and social media environments: An empirical analysis through Hawkes’ models and natural language processing

Abstract

We analyse, using a mixture of statistical models and natural language process techniques, what happened in social media from June 2019 onwards to understand the relationships between Cryptocurrencies’ prices and social media, focusing on the rise of the Bitcoin and Ethereum prices. In particular, we identify and model the relationship between the cryptocurrencies market price changes, and sentiment and topic discussion occurrences on social media, using Hawkes’ Model. We find that some topics occurrences and rise of sentiment in social media precedes certain types of price movements. Specifically, discussions concerning governments, trading, and Ethereum cryptocurrency as an exchange currency appear to negatively affect Bitcoin and Ethereum prices. Those concerning investments, appear to explain price rises, whilst discussions related to new decentralized realities and technological applications explain price falls. Finally, we validate our model using a real case study: the already famous case of ”Wallstreetbet and GameStop”11 https://www.economist.com/finance-and-economics/2021/02/06/how-wallstreetbets-works. that took place in January 2021.

Keywords

• Cryptocurrencies
• Social media analysis
• Fundamental analysis
• Forecasting price movements
• Hawkes model