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Fake News Detection of COVID-19 on Twitter Platform: A Review

	International Journal of Scientific Research and Engineering Development (IJSRED)	Full Text:
	Published Issue : Volume-4 Issue-1
	Year of Publication : 2021
	Unique Identification Number : IJSRED-V4I1P65
	Authors : Khansa Rana, Dr. Hamid Ghous
	: Click Here | DOI : https://doi.org/10.5281/zenodo.4536673

Abstract :

In the 21st century, it was found that rather than conventional media such as print media, a larger number of participants consumed news from search engines and social media. The goal of this research is to examine the false news on the Twitter platform connected to COVID-19. A difficult task for humans is to recognize such false facts. Many researchers faced difficulties to identify the issue statements and their attributes in describing fake news. Attempts have been devoted to addressing this issue with techniques of deep learning and machine learning. In fake news identification, the effect of linguistic features and contextual characteristics areanalysed and some techniques such as Naive Bayes, Decision tree, Hybrid CNN, KNN, and SVMare compared. This study reviewed the current and past literature suggested by the researchers to detect fake news.Approaches are based on content types (textual or image-based) to overcome the problem more smartly and to achieve enhanced classification results.The main purpose of this paper is to review literature for COVID-19 fake news detection on Twitter using machine learning and deep learning method.