Incorporating sentiment analysis of social media data, this research aims to develop a stock price prediction model that provides valuable insights for investors and enhances decision-making in trading activities. This study investigates the relationship between public perceptions expressed on social media and changes in stock prices. By employing sentiment analysis on publicly available data for a sample stock, we analyze and assess the sentiment (positive, negative, or neutral). These sentiment scores are then used for future stock price prediction. The paper used the Random Forest Model to predict the future stock prices. The study also shows the results before and after adding the sentiment polarity as an independent variable. The accuracy score of the model improved from 52 to 82.77% after sentiment polarity was added. The findings of the study showed that there is a strong association between the stock prices and the opinions that public share in social media platforms. The study provides a strong indication that investors’ decision to buy, hold, or sell shares should incorporate public opinion in addition to the traditional price trend and volume metrics.