Automated Trading of Cryptocurrency Using Twitter Sentimental Analysis - Chheda, SR; Singh, AK; Singh, PS; Bhole, AS (International Journal of Computer Sciences and Engineering, 2025)
Twitter is one of the most used social networking sites where millions of people give their opinions about various subjects. Thus it can be treated as one of the largest and most updated psychological database. Analysis can be performed on this data to gain valuable insights. The goal of this paper is to study the correlation between public opinion about the Cryptocurrency, Bitcoin and the trajectory of its price graph. The results can later be used to develop a system for algorithmic trading of Bitcoin. This is done by collecting tweets on bitcoin and performing sentimental analysis on it. The tweets are labelled positive or negative. Supervised machine learning algorithms are used to see how sentiments of tweets play a role in bitcoin market movement. A positive sentiment and an increase in the price of bitcoin at the same time will indicate selling as favourable and vice versa in case of a negative polarity of tweets.