Analyzing the Dynamics of Cryptocurrency Rate of Return through Social Media for Financial Trends

In recent times, a significant increase in research focus and the consideration of cryptocurrencies as an asset by institutional investors. Due to its volatility and influence on numerous outside variables, it has become a challenge to estimate its values. The proposed work investigates the impact of social media sentiment on the fluctuations related to cryptocurrency market, specifically emphasis on Bitcoin, Ether, and Binance, using data from Twitter and Telegram between July 19, 2023, and July 19, 2024. Firstly, an analysis is conducted using the covariance and correlation between the cryptocurrency return. After analysis, time series models Autoregressive integrated moving average and Seasonal Autoregressive Integrated Moving Average (ARIMA, SARIMA), and machine learning models (LSTM and Bi-LSTM) are employed to analyze and predict cryptocurrency return rate using the data. Finally, Hazards associated with trading in every cryptocurrency are examined with the help of value potential data. The results indicate that Twitter, due to its concise and real-time characteristics, provides more immediate insights into price changes, making it particularly advantageous for short-term trading strategies. Conversely, Telegram encompasses a wider range of market sentiment, reflecting varied discussions that are beneficial for trend analysis and long-term forecasting, albeit with a higher level of noise. Both LSTM and Bi-LSTM models exhibited robust predictive capabilities, although the outcomes differed among various cryptocurrencies and platforms. Sentiment data from Twitter was found to correlate more closely with short-term price fluctuations, while Telegram's data offered a more holistic perspective on market trends. The study concludes that combining sentiment insights from both platforms can improve predictive accuracy, utilizing Twitter’s immediacy alongside Telegram’s comprehensive insights, thus facilitating more informed trading and investment choices in the dynamic cryptocurrency market.