Stock market prediction algorithms were compared using Twitter data to help investors make better decisions. The study used historical stock prices and tweet comments to predict stock market status. Four methods were tested: Linear Regression, Support Vector Machine, Naïve Bayes, and Random Forest. Results showed that the Support Vector Machine method had the best predicting performance compared to the others. This comparison can help investors decide when to buy stocks.