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Sentiment Analysis using Improved Vader and Dependency Parsing

Publication Type : Conference Proceedings

Publisher : IEEE

Source : 2021 2nd Global Conference for Advancement in Technology (GCAT)

Url :

Campus : Amritapuri

School : School of Computing

Department : Computer Science and Engineering

Year : 2021

Abstract : We know, one Act has been initiated by the Government of India in September 2020, often known as Farm Bills or Indian Agricultural Act. This act has been affected farmers in many ways and led to opposition to the bills. As a result, there is a wide area for doing sentiment on the data taken from this domain, so we are making sentiment analysis on it. On comparing different algorithms like Logistic Regression, VADER, and BERT, we could see that BERT is having more accuracy as compared to the other algorithms. But we could see that VADER is a good algorithm as they are having special qualities as compared to that of the other algorithm. So, we thought to Improve VADER (Valence Aware Dictionary and sEntiment Reasoner) sentiment analysis on Farm Bill Act. Along with this, we are doing Information Extraction on verb and analyzing sentiments on extracted phrases that are related to the verb, to get the accuracy of sentences with verb and without verb. Thus, we get the Dependency of the verb in the sentence.

Cite this Research Publication : G Veena; Aadithya Vinayak; Anu J Nair, "Sentiment Analysis using Improved Vader and Dependency Parsing," 2021 2nd Global Conference for Advancement in Technology (GCAT), 2021, pp. 1-6, doi: 10.1109/GCAT52182.2021.9587829.

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