Analysis of Human Behaviour on Movie Review

Study of all aspects of society requires an in-depth study of how people behave, and the world of movie reviews is one place where this may be done. The goal of the project is to obtain a greater understanding of how people communicate their thoughts, preferences, and attitudes about movies by gleaning insightful information from a vast corpus of movie reviews. The main goal is to identify patterns, trends, and underlying causes that affect people’s conduct when rating movies. We offer a variety of techniques for extracting textual features, including the bag-of-words model, a sizable corpus of movie reviews, limiting to adjectives and adverbs, and managing negations. You can ascertain someone’s feelings on a specific material source using this technique. There is enormous amounts of information available primarily through tweets, blogs, status updates, postings, and other online platforms like social media. This study analysed movie reviews using a variety of techniques, such as Naive Bayes (NB), K-Nearest Neighbour (K-NN), as well as Random Forest (RF). The study advances our understanding of human behaviour analysis, especially in the field of film criticism. The knowledge gathered from this research may open up new avenues for investigation and the creation of intelligent systems that can more accurately forecast and understand human preferences, facilitating decision-making across the entertainment sector.