Ahmed, ErfanSazzad, Md. Asad UzzamanIslam, Md. TanzimAzad, MuhitunIslam, SamiulAli, Mohammad Haider2026-09-082026-09-082017-10-17E. Ahmed, M. A. U. Sazzad, M. T. Islam, M. Azad, S. Islam and M. H. Ali, "Challenges, comparative analysis and a proposed methodology to predict sentiment from movie reviews using machine learning," 2017 International Conference on Big Data Analytics and Computational Intelligence (ICBDAC), Chirala, Andhra Pradesh, India, 2017, pp. 86-91, doi: 10.1109/ICBDACI.2017.8070814.97815090639942-s2.0-85040175900https://hdl.handle.net/10361/29818This paper investigates a new approach of finding sentence level sentiment analysis using different machine learning algorithms. Three different machine learning algorithms - SVM (Support Vector Machine), Naïve Bayes and MLP (Multilayer Layer Perceptron) have been used both for sentiment analysis. Moreover two different classifiers of Naïve Bayes and two different types of SVM kernels have been used in this work to identify and analyze the difference in accuracy as well as to find the best outcome among all the experiments. For sentiment analysis aclimdb movie review dataset has been used. Lastly, the impact of stop words and number of attributes in accuracy for sentiment analysis has also been illustrated.6 Pagesen-USKernelSupport vector machinesMotion picturesSentiment analysisMachine learning algorithmsClassification algorithmsComputer scienceNaïve bayesSentiment analysis.Natural language processing (Computer science).Conference Proceeding10.1109/ICBDACI.2017.8070814