A Machine Learning-Based Platform for Sentiment Analysis of Movie Reviews

Doosuur S. Kwaghzan

doi:10.56201/ijcsmt.vol.11.no12.2025.pg16.23

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A Machine Learning-Based Platform for Sentiment Analysis of Movie Reviews

Doosuur S. Kwaghzan

Abstract

Sentiment analysis is the computational study of opinions and attitudes expressed in text. With the rapid growth of online reviews, especially in the film industry, it has become increasingly difficult to process user-generated content for decision-making. This study presents a sentiment analysis management platform designed to classify and visualize user opinions on movie reviews. A Facebook page was created to collect 25,000 comments from 20 adventure films, which served as the dataset. Using Python, the system implemented supervised and unsupervised learning approaches, with logistic regression and support vector machines tested against existing movie review corpora. Classification was performed on the basis of subjectivity and polarity, producing visual outputs to support fast decision-making. Experimental results demonstrated a classification accuracy of 88.1 percent, indicating the effectiveness of the platform in managing large-scale opinion data.

Keywords

sentiment analysismovie reviewsnatural language processingmachine learningtext classification

References

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A Machine Learning-Based Platform for Sentiment Analysis of Movie Reviews

Abstract

Keywords

References

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