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Please use this identifier to cite or link to this item: http://lrcdrs.bennett.edu.in:80/handle/123456789/810
Title: PSent20: An Effective Political Sentiment Analysis with Deep Learning Using Real-Time Social Media Tweets
Authors: Garg, Apar
Kaliyar, Rohit Kumar
Keywords: Neural Network; Sentiment Analysis; Social Media; Text Classification
Issue Date: Dec-2020
Publisher: IEEE
Abstract: In the current era of computing, the use of social networking sites like Twitter and Facebook, is growing significantly over time. People from different cultures and backgrounds share vast volumes of textual comments that show their viewpoints on several aspects of life and make them available to all for commenting. Monitoring real social media activities has now become a prime concern for politicians in understanding their social image. In this paper, we are going to analyse the tweets of various social media platforms regarding two prominent political leaders and classify them as positive, negative or neutral using Machine Learning and Deep Learning methods. We have proposed a Deep Learning approach for a better solution. Our proposed model has provided state-of-the-art results using Deep Learning models. © 2020 IEEE.
Description: https://ieeexplore.ieee.org/document/9358379
URI: http://doi.org/10.1109/ICRAIE51050.2020.9358379
http://lrcdrs.bennett.edu.in:80/handle/123456789/810
ISBN: 9781728188676
Appears in Collections:Conference Proceedings_ SCSET

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