REVIEW ON SENTIMENT ANALYSIS IN TAMIL TEXTS

Show simple item record

dc.contributor.author Sajeetha Thavareesan, Sinnathamby Mahesan
dc.date.accessioned 2019-06-27T09:06:29Z
dc.date.available 2019-06-27T09:06:29Z
dc.date.issued 2018
dc.identifier.issn 2602-9030
dc.identifier.uri http://www.digital.lib.esn.ac.lk/handle/123456789/3850
dc.description.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. en_US
dc.language.iso en en_US
dc.publisher Faculty of Science, Eastern University, Sri Lanka en_US
dc.subject Sentiment Analysis (SA) en_US
dc.subject Natural Language Processing (NLP) en_US
dc.subject Tamil en_US
dc.subject machine learning en_US
dc.title REVIEW ON SENTIMENT ANALYSIS IN TAMIL TEXTS en_US
dc.type Article en_US
dc.identifier.sslno 9.2.1 en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search Gateway


Browse

My Account