Review on sentiment analysis in Tamil texts

Sajeetha Thavareesan,Sinnathamby Mahesan

doi:10.4038/jsc.v9i2.14

Abstract

Sentiment Analysis (SA) is an application of Natural Language Processing (NLP) to analyse the sentiments expressed in the text. It classifies into categories of qualities and opinions such as good, bad, positive, negative, neutral, etc. It employs machine learning techniques and lexicons for the classification. Nowadays, people share their opinions or feelings about movies, products, services, etc. through social media and online review sites. Analysing their opinions is beneficial to the public, business organisations, film producers and others to make decisions and improvements. SA is mostly employed in English language but rare for Indian languages including Tamil. This review paper aims to critically analyse the recent literature in the field of SA with Tamil text. Objectives, Methodologies and success rates are taken in consideration for the review. We shall conclude from the review that SVM and RNN classifiers taking TF-IDF and Word2vec features of Tamil text give better performance than grammar rules based classifications and other classifiers with presence of words, TF and BoW as features.

Highlights

Social media and e-commerce have a great impact on human life, especially with the high usage of smartphones all over the world
Random Kitchen Sink (RKS) and Multinomial Naive Bayes (MNB) can be employed for Sentiment Analysis (SA) in Tamil as they yielded above 61% which is comparably closer to the accuracy of SVM
When analysing the elapsed time, RKS yielded lowest when compared to MNB and SVM

Summary

Introduction

Social media and e-commerce have a great impact on human life, especially with the high usage of smartphones all over the world. These facilitate the users to share and access the opinions of individuals around the world. This makes an explosive growth of data in the internet. Opinions are the key influences to almost all human activities and behaviours. We seek opinions before we make decisions. People rely only on their friends and relatives for opinions and comments about anything they wanted. When a business organisation needed public opinions about its products and services, it conducted surveys and opinion polls, which is a tedious, time consuming and costly matter [1]

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Conclusion