Result Analysis on Twitter Sentiment Analysis using BERT Algorithm

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SAMRUDDHI MANOJ MAHALLE; DR V. S. GULHANE; DR AVINASH P. JADHAO

Result Analysis on Twitter Sentiment Analysis using BERT Algorithm

Authors: SAMRUDDHI MANOJ MAHALLE, DR V. S. GULHANE, DR AVINASH P. JADHAO

Unique Paper ID: 161238
Volume: 10
Issue: 3
PageNo: 11-19

Keywords: BERT Sentiment Twitter Django Deep Learning.

Abstract:
With the exponential growth of web technology and the increasing popularity of social networking sites like Twitter, there has been an unprecedented volume of user-generated data available on the internet. The diverse nature of opinions and sentiments expressed in tweets presents a unique opportunity for sentiment analysis, where understanding the emotions and attitudes of users towards various topics becomes crucial. Sentiment analysis on Twitter is a challenging task due to the unstructured and heterogeneous nature of the content, which can be positive, negative, or neutral in different contexts. In this paper, we present a comprehensive survey and comparative analysis of existing techniques for sentiment analysis, with a focus on utilizing the BERT (Bidirectional Encoder Representations from Transformers) model, a cutting-edge deep learning approach.

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Cite This Article

ISSN: 2349-6002
Volume: 10
Issue: 3
PageNo: 11-19

Result Analysis on Twitter Sentiment Analysis using BERT Algorithm

Available:https://ijirt.org/article?manuscript=161238

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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