DETECTION OF FAKE NEWS IN SOCIAL NETWORKS BY MACHINE LEARNING
Ms. Supriya Ashok Bhosale¹, Dr. Lokendra Singh Songare²
1Student, Department of Computer Science & Engineering, Dr. A. P. J. Abdul Kalam University, Indore, MP, India
2Assistant Professor, Department of Computer Science & Engineering, Dr. A. P. J. Abdul Kalam University, Indore, MP, India
The Internet is widely used by a large number of people, making it one of the most important inventions of all time. These people put this to a number of uses. This group of people has access to a wide range of social media platforms. In our digital age, anyone with an internet connection can publish anything they want. These platforms do not verify users’ posts or identities. As a result, some people are using these platforms to spread misleading information. They can target an individual, a team, or even an entire political party. It is impossible for a human being to tell the difference between real and fake news. It is therefore necessary to use machine learning-trained classifiers in order to detect fake news. In this extensive research review, the use of machine learning classifiers for detecting false news is described.
Keywords: Fake News, Machine learning, Text Classification, social media.