Fake News Detection with Machine Learning
Jayesh Patel1, Melroy Barreto2, UtpalSahakari3, Supriya Patil4

1Jayesh Patel, Associate professor in Electronics and Telecommunication Engineering Department at Padre Conceicao College of Engineering, Verna, Goa. India.
2MelroyBarreto, Associate professor in Electronics and Telecommunication Engineering Department at Padre Conceicao College of Engineering, Verna, Goa. India.
3UtpalSahakari, Associate professor in Electronics and Telecommunication Engineering Department at Padre Conceicao College of Engineering, Verna, Goa. India.
4Dr. Supriya Patil, Associate professor in Electronics and Telecommunication Engineering Department at Padre Conceicao College of Engineering, Verna, Goa. India.

Manuscript received on September 18, 2020. | Revised Manuscript received on November 06, 2020. | Manuscript published on November 10, 2021. | PP: 124-127 | Volume-10 Issue-1, November 2020 | Retrieval Number: 100.1/ijitee.A80901110120| DOI: 10.35940/ijitee.A8090.1110120
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: As the internet is becoming part of our daily routine there is sudden growth and popularity of online news reading. This news can become a major issue to the public and government bodies (especially politically) if its fake hence authentication is necessary. It is essential to flag the fake news before it goes viral and misleads the society. In this paper, various Natural Language Processing techniques along with the number of classifiers are used to identify news content for its credibility. Further this technique can be used for various applications like plagiarismcheck , checking for criminal records. 
Keywords: K-Means Cluster (K-means), K-Nearest neighbor (KNN), Stochastic Gradient Descent (SGD),Support Vector Machines (SVM).