fake news detector using machine learning
S. SRINIVASAN,M. SANJAY,A. KASEELAN,B ARUNMOZHI , M.E.
Published in International Journal of Advanced Research in Computer Science Engineering and Information Technology
ISSN: 2321-3337 Impact Factor:1.521 Volume:6 Issue:3 Year: 02 April,2021 Pages:1508-1514
Abstract
The advent of the World Wide Web and the rapid adoption of social media platforms paved the way for information dissemination that has never been witnessed in the human history before. With the current usage of social media platforms, consumers are creating and sharing more information than ever before, some of which are misleading with no relevance to reality. In this work, we propose to use machine learning ensemble approach for automated classification of news articles.
Kewords
news, fake news
Reference
D. M. J. Lazer, M. A. Baum, Y. Benkler et al., “The science of fake news,” Science, vol. 359, no. 6380, pp. 1094– 1096, 2018.View at: Publisher Site | Google Scholar 2. S. Kogan, T. J. Moskowitz, and M. Niessner, “Fake News: Evidence from Financial Markets,” 2019, https://ssrn.com/abstract=3237763.View at: Google Scholar 3. J. Hua and R. Shaw, “Corona virus (covid-19) “infodemic” and emerging issues through a data lens: the case of China,” International Journal of Environmental Research and Public Health, vol. 17, no. 7, p. 2309, 2020.View at: Publisher Site | Google Scholar 4.F. T.AsraandM. Taboada, “Misinfotext: a collection of news articles, with false and true labels,” 2019.View at: Google Scholar 5. H. Jawa, D. Oh, K. Park, J. M. Kang, and H. Lim, “exBAKE: automatic fake news detection model based on bidirectional encoder representations from transformers (bert),” Applied Sciences, vol. 9, no. 19, 2019.View at: Publisher Site | Google Scholar.
