  The Web is a vast virtual space where people can share their opinions,
impacting all aspects of life and having implications for marketing and
communication. The most up-to-date and comprehensive information can be found
on social media because of how widespread and straightforward it is to post a
message. Proportionately, they are regarded as a valuable resource for making
precise market predictions. In particular, Twitter has developed into a potent
tool for understanding user sentiment. This article examines how well tweets
can influence stock symbol trends. We analyze the volume, sentiment, and
mentions of the top five stock symbols in the S&P 500 index on Twitter over
three months. Long Short-Term Memory, Bernoulli Na\"ive Bayes, and Random
Forest were the three algorithms implemented in this process. Our study
revealed a significant correlation between stock prices and Twitter sentiment.
