Abstract
Classifying texts based on sentiments present in the text is called Sentiment Analysis. There are many Sentiment Analysis Techniques available. In this paper, we have addressed the problem of sentiment analysis and compared many different machine learning and deep learning algorithms to perform sentiment analysis based on their accuracy. We extracted useful features to feed them in our classifier to generate results. Also, we have used the majority vote ensemble method to achieve more accurate results.
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Kumar, A., Khare, M., Tiwari, S. (2022). Comparative Evaluation on Sentiment Analysis Algorithms. In: Mambo, A.D., Gueye, A., Bassioni, G. (eds) Innovations and Interdisciplinary Solutions for Underserved Areas. InterSol 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 449. Springer, Cham. https://doi.org/10.1007/978-3-031-23116-2_9
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