International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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IMDb Sentiment Analysis Using Naive Bayes :Multinomial and Bernoulli Models with LaplaceSmoothing and 5-Fold Cross Validation

Author(s) Prof. Lija Mishra
Country India
Abstract This study presents a sentiment analysis system for IMDb movie reviews using Multinomial and Bernoulli Naive Bayes classifiers with Laplace smoothing. After preprocessing text data, both models were evaluated using 5-fold cross-validation. Results show that Multinomial Naive Bayes outperforms Bernoulli Naive Bayes, achieving higher accuracy and better handling of word frequency information in long textual reviews.
Keywords Sentiment Analysis, IMDb Dataset, Multinomial Naive Bayes, Bernoulli Naive Bayes, Laplace Smoothing, Natural Language Processing (NLP), Machine Learning, Text Classification, Cross-Validation
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 6, November-December 2025
Published On 2025-11-13
DOI https://doi.org/10.36948/ijfmr.2025.v07i06.60198
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E-ISSN 2582-2160
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