Sentimental Analysis of Movie Reviews Using Machine Learning

Sentiment analysis is a rapidly growing field in natural language processing that aims to extract subjective information from text data. One of the most common applications sentiment movie industry, where it used gauge public opinion on films. In this research paper, sentimental reviews has been presented using dataset over 25,000 collected various sources. A machine learning model with different classifiers was built Naïve Bayes, Logistic Regression and Support Vector Machines for classifying as positive, negative or neutral. comparison three popular algorithms made. After pre-processing by removing stop words, stemming technique applied reduce dimensionality dataset. The recognition were evaluated terms performance matrices such accuracy, precision, recall F1-score. Compared others, observed SVM algorithm performed best among all algorithms, achieving an accuracy 73%. results demonstrated effectiveness accurately provided valuable insights into current state insight be specific scenario.