AN EXPERIMENTAL ANALYSIS OF DEEP NEURAL NETWORK BASED CLASSIFIERS FOR SENTIMENT ANALYSIS TASKS
Keywords:
Sentiment classification, Neural Language Model, Machine Learning, Natural Language Processing, Textual Data, Opinion Mining, Topic AugmentationAbstract
The proliferation of social mediaplatforms and online communities has given rise toa pressing concern-the proliferation of fake profiles.We propose the development of an Artificial NeuralNetwork system, a machine learning
References
L. Li, D. Novillo-Ortiz, N. Azzopardi-Muscat, and P. Kostkova, ‘‘Digital data sourcesand their impact on people’s health: A systematic review of systematic reviews,’’ Frontiers Public Health, vol. 9,
May 2021, Art. no. 645260. Accessed: Sep. 1, 2022. [Online].
Y. Gorodnichenko, T. Pham, and O. Talavera, ‘‘Social media, sentiment and public opinions: Evidence from #Brexit and #USElection,’’ Eur.
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Published
2024-02-15
How to Cite
Dr. D. Madhavi, Margam Bhavana, Kappari Neha sree, Mallela Pragathi. (2024). AN EXPERIMENTAL ANALYSIS OF DEEP NEURAL NETWORK BASED CLASSIFIERS FOR SENTIMENT ANALYSIS TASKS. Journal of Computational Analysis and Applications (JoCAAA), 32(2), 309–318. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/2705
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