Abstract
Nowadays, many organizations use customer reviews to improve their business. They analyze the reviews given by the customer to get a concrete decision about the quality of the products or services provided by them. Sentiment Analysis in recent times has come up in a broad way for the analysis of the customer reviews and comments to know the customer views regarding consumer products or services. Through sentiment analysis, the attitude of the customers toward the product can be easily determined. In this paper, we used movie reviews dataset to extract the sentiment of viewers using machine learning approaches. We have used Word2Vec feature extraction method to obtain features from movie reviews. An arithmetic mean of the word vectors is obtained along each dimension and, thereafter, the same mean vector is used to train the different machine learning classifiers. The same method is used on performance classifiers against the available test data. Our proposed model yields an overall good performance based on accuracy, recall, and F1 score. Finally, we made a comparative analysis, among various methods used here based on their performance.
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Khan, A., Majumdar, D., Mondal, B. (2021). Machine Learning Approach to Sentiment Analysis from Movie Reviews Using Word2Vec. In: Pan, I., Mukherjee, A., Piuri, V. (eds) Proceedings of Research and Applications in Artificial Intelligence. Advances in Intelligent Systems and Computing, vol 1355. Springer, Singapore. https://doi.org/10.1007/978-981-16-1543-6_12
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DOI: https://doi.org/10.1007/978-981-16-1543-6_12
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