Application to Detect Fake News Using Machine Learning Algorithms

  • Sini Anna Alex, Aditya Singh Tomar, Daniel Monteiro, Zaid Hossain, Zubin Paymaster

Abstract

Develop a machine learning program to identify when a news source may be producing fake news. We aim to use a corpus of labeled real and fake new articles to build a classifier that can make decisions about information based on the content from the corpus. The model will focus on identifying fake news sources, based on multiple articles originating from a source. Once a source is labeled as a producer of fake news, we can predict with high confidence that any future articles from that source will also be fake news. Focusing on sources widens our article misclassification tolerance, because we will have multiple data points coming from each source. An application will be built based on this machine learning program in order to increase accessibility to detection of fake news.

Published
2020-03-30
How to Cite
Sini Anna Alex, Aditya Singh Tomar, Daniel Monteiro, Zaid Hossain, Zubin Paymaster. (2020). Application to Detect Fake News Using Machine Learning Algorithms. International Journal of Advanced Science and Technology, 29(3), 12164 - 12173. Retrieved from https://sersc.org/journals/index.php/IJAST/article/view/30308
Section
Articles