Bitcoin User

Bitcoin user behavior is a multifaceted research area aiming to understand user activity, influence, and the impact of this activity on market dynamics and security. Current research focuses on applying machine learning models, including neural networks, random forests, and graph neural networks, to analyze transaction data, social media sentiment (particularly Twitter), and other relevant factors to predict price movements, detect illicit activities like money laundering and selfish mining, and assess market efficiency. These analyses provide valuable insights into Bitcoin's ecosystem, informing both the development of improved trading strategies and enhanced security measures against malicious actors.