Sentiment analysis of IMDB movie review with machine learning
Sapandeep Singh Sandhu, Jarnail Singh · 2023
Sentiment analysis is an estimation of the people, speakers, or writers concerning any topic. Nowadays, social media is viral. People use it to interact with people and exchange their thoughts on any topic, happenings, products, and other services. IMDB, known as Internet movie database, is the most popular online source of movies, TV shows, and celebrity content. It was launched online in 1990. It is an online database providing information related to entertainment, ratings, or reviews of movies. Various machine learning algorithms may be used categories its information primarily based totally on their sentiments. This paper implements the sentiment analysis of IMDB movie review. A trained dataset from the IMDB database used. After analyzing the data, prediction of the number of negative and positive reviews based on sentiments by using different classification models. The implementation of this system Python with SKlearn, NLTK, Bags of words model, term frequency- inverse document frequency model is applied. Also, the word cloud is plotted, showing the most frequently appearing positive and negative comments in the review.