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Paper Title : OMICRON VARINAT SENTIMENT ANALYSIS USING NLP TECHNIQUE

ISSN : 2395-1303
Year of Publication : 2022
10.5281/zenodo.7295142

Authors: G.Akshitha, E.Jagruthi, B.Akhila

         


Abstract
Twitter is a micro-blogging website which provides platform for people to share and express their views about topics, happenings, products and other health issues. Tweets can be classified into different classes based on their relevance with the topic searched. NLP for health- related queries are currently employed in classification of tweets into positive and negative classes based on their sentiments using natural language processing techniques. This paper contains implementation of NLP for message classification based on twitter omicron tweets data set using sentiment140 training data using twitter database and propose a method to improve classification. Use of Lemmatization along with NLP can improve accuracy of classification of tweets, by providing positivity, negativity and objectivity score of words present in tweets. For actual implementation of this system python with NLP and twitter data set are used. In this paper we are using sentiments analysis in twitter tweets for omicron datasets in order to classify the reviews of all users whether it is positive, negative or neutral

Reference
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Keywords
— OMICRON VARINAT SENTIMENT ANALYSIS USING NLP TECHNIQUE