Researchers developed a new method to predict the sales price of cars using news sentiment analysis and a Random Forest algorithm. They compared different classifiers like Naive Bayes and Random Forest on a dataset of stock sentiment scores. The Random Forest classifier was found to be more accurate, predicting future stock prices at a rate of 92% compared to Naive Bayes at 87%. This suggests that the Novel Random Forest approach is better for predicting stock market trends.