Abstract

Sentiment analysis is the process of extracting information from the given text in which the text consists of various sensations such as happiness, perturbation, pride, worry, and so on about various functions, human beings, systems, and facts. Sentimental analysis or opinion mining uses data mining and natural language processing techniques to discover, retrieve and filter the information and opinions from the World Wide Web’s vast textual information. The sentiment analysers for European languages and some Indic languages are fully developed. However, Tamil, which is an under-resourced language with rich morphology, has not experienced these advancements. A few experiments have been conducted to determine the sentiments for Tamil text. An approach to doing the sentiment analysis for the Tamil language is proposed in this paper. The proposed approach uses Long Short-Term Memory, Convolutional Neural networks, and simple Deep Neural Network techniques. Test results show that the Long Short-Term Memory-based deep learning model performs well than the Convolutional Neural Network and simple Deep Neural Network for sentiment analysis of Tamil language with 94.10% accuracy.

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