Indian Journal of Science and Technology
Year: 2024, Volume: 17, Issue: 7, Pages: 610-616
Original Article
Radha Krishna Jana1*, Dharmpal Singh1, Saikat Maity2, Hrithik Paul1
1Department of Computer Science & Engineering, JIS University, Kolkata, India
2Department of Computer Science & Engineering, Sister Nivedita University, Kolkata, India
*Corresponding Author
Email: [email protected]
Received Date:26 November 2023, Accepted Date:13 January 2024, Published Date:08 February 2024
Objectives: The objective of this study is to introduce a hybrid model for analyzing the people sentiment on covid-19 tweets. Methods: We used a total no. of 27,500 datasets, 70% of the data sets for training and reserved the other 30% for testing. Due to this separation 19,250 samples are used for training, the remaining 8,250 were used to evaluate the accuracy of the test. This paper proposes a technique for sentiment analysis that integrates deep learning, genetic algorithms (GA), and social media sentiment. For more accuracy and performance, we here suggested a hybrid genetic algorithm-based model. A hybrid model is created by assembling the LSTM model and providing it to the genetic algorithm architecture. Findings: LSTM with a genetic model better than LSTM without genetic model. The accuracy of our suggested model is 96.40%. Novelty : The accuracy of the LSTM model for sentiment analysis is 91%. The accuracy of the proposed model is 96.40%. The proposed model is more accurate for sentiment prediction.
Keywords: Social network perception, Crossover, Mutation, LSTM, NLP, GA
© 2024 Jana et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)
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