Predicting Ethereum Price Fluctuations Using Sentiment Analysis and Machine Learning

Predicting Ethereum Price Fluctuations Using Sentiment Analysis and Machine Learning

*Kamal B. Pandey, Student & Undergraduate Researcher, Department of Computer Science & Engineering,

Parul University, Vadodara, India
*Ayush M. Patel, Student & Undergraduate Researcher, Department of Computer Science & Engineering,

Parul University, Vadodara, India

*Nidhi Pandey, Assistant Professor & Research Guide, Department of Computer Science & Engineering,

Parul University, Vadodara, India

*Anand Kumar Singh, Assistant Professor & Research Guide, Department of Computer Science & Engineering,

Parul University, Vadodara, India

Department of Computer Science & Engineering, Parul University, Vadodara, India
*email address of corresponding author

Keywords: Ethereum Predictions, Sentiment Analysis, Cryptocurrency Market, Price Forecasting, Google Trends,

Twitter Analysis, Support Vector Machine, Machine Learning

Abstract

This study examines the ability to anticipate the fluctuations of Ethereum prices using sentiment analysis and machine learning advanced techniques. Ethereum blockchain data: Being the second largest cryptocurrency globally, ranked by market capitalization, analyzing Ethereum’s blockchain data can prove useful for predicting price movements. We will try to take advantage of social media sentiment, specifically Twitter, and use machine learning methods including linear regression, logistic regression, and support vector machines. Combining sentiment data, the goal is to enhance the models designed for sentiment analysis with quantitative financial data and to increase the accuracy of our predictions.