Twitter Scraping and Sentiment Analysis on Stock Price

social media is useful in the community for sharing and discussing various events with others. The study's main objective is to predict the sign of the stock by sentimental analysis regarding the Hindenburg report on Adani group stocks by obtaining tweets from Twitter. The study's findings will aid in understanding the effect of the Hindenburg report on the stocks of the Adani group. Excel files are downloaded from Twitter containing tweets from social media users. Tweets are cleaned up by eliminating noise data after extraction. Machine learning algorithms, such as Logistic Regression (LR), Linear support classification (SVC), Random Forest (RF), and voting, were used to classify the data into positive, Neutral, and negative groups.