Stock Market Prediction using Sentiment Analysis and Machine Learning Approach

A speculator is behind every dollar traded in the market, just as billions of dollars are exchanged daily. Market conduct determines the fate of entire organizations each day. Financial specialists have always strived to anticipate the Stock Market since it has existed. Financial markets are now beginning to use and test the sentiment analysis-based ML approach. It is a tempting guarantee of riches and influence for a financial specialist to have the capability to anticipate trend changes precisely. When they get out of hand, stock Market problems and their related difficulties have no trouble finding their way to the open creative mind. A vital purpose of this study is to identify the best model to predict currency trading estimation. With the growing interest in artificial intelligence, and during the selection of methodologies and elements to consider, it was found that standard algorithms like random forests and SVMs weren't fully exploited to address this challenge, which is why the researchers used sentiment analysis-based ML approach, the Artificial Neural Networks (ANNs) and Support Vector Machines (SVMs), which can be used to forecast stocks. In the following discussion, a comparison of SVM ML approaches and traditional forecasting methods was conducted to estimate stocks' market value.