Abstract
Applying sentiment analysis to mine the huge amount of unstructured data in social media has become an important field of research. Businesses and organizations have shown growing interests. Sentiment analysis can help understand the end user’s opinion about a given topic. Movie reviews represent a large amount of opinionated data which reflect feelings and emotions about a particular movie. The objective of this work is to develop a domain-specific sentiment classifier which is capable of identifying sentiment expressed in these reviews. We developed a sentiment analysis model based on movie reviews which achieved a 90% accuracy. Logistic regression, support vector machines, and multinomial naive Bayes learning algorithms along with various text preprocessing algorithms were used. Support vector machine algorithm gave the best results achieving 90% accuracy.
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Carvalho, B., Urolagin, S. (2021). A Comparison of Sentiment Analysis Techniques on Movie Reviews. In: Gao, XZ., Kumar, R., Srivastava, S., Soni, B.P. (eds) Applications of Artificial Intelligence in Engineering. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-33-4604-8_44
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DOI: https://doi.org/10.1007/978-981-33-4604-8_44
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