Utilizing Machine Learning for Sentiment Analysis of IMDB Movie Review Data

Research led by Ustad Ubaid Mohamed Dahir discussed using machine learning techniques for sentiment analysis of IMDB movie review data. By employing natural language processing and feature extraction, they develop sentiment classification models to analyze opinions expressed in vast amounts of text data. The findings demonstrate the effectiveness of logistic regression with TF-IDF in minimizing false positives, contributing to improved sentiment analysis and more accurate text analytics tools. Overall, sentiment analysis in the film industry has numerous applications, from helping consumers make informed decisions about which movies to see to assisting film production firms in predicting a film’s financial success. With the advent of big data and the increasing availability of natural language processing and machine learning techniques, sentiment analysis is becoming more accurate and effective.
Read the full article here… Utilizing Machine Learning for Sentiment Analysis of
IMDB Movie Review Data