As people’s demand for easy access to information grows, they increasingly use social media platforms like Twitter and Facebook to share, provide, and seek information. Every second, Twitter users send a vast number of tweets, which can be transformed into valuable information through sentiment analysis. A rapid and accurate classification model is needed to analyze large volumes of tweets, and this approach can be applied to stock price projections based on market-related tweets. Accurately predicting stock investment strategies is a significant challenge for investors. This paper uses sentiment analysis to develop models supporting investment decision-making in the Indian stock market. By employing the VADER model, we forecast investment strategies, arguing that sentiment analysis of headlines and tweets influences stock market values. During the research period, we collected headlines and stock market investment data, finding that the model accurately predicts investment strategies when applied to Sensex.