An Effecient Fake News Detection System Using Machine Learning
A. Lakshmanarao1, Y. Swathi2, T. Srinivasa Ravi Kiran3
1A. Lakshmanarao, Department of Computer Science & Engineering, Raghu Engineering College, Visakhapatnam, A. P, India.
2Y. Swathi, Department of Computer Science & Engineering, BABA Institute of Technology & Sciences, Visakhapatnam, A.P, India.
3Dr. T. Srinivasa Ravi Kiran, Department of Computer Science, P.B. Siddhartha College of Arts & Science Vijayawada, India.
Manuscript received on 01 August 2019 | Revised Manuscript received on 05 August 2019 | Manuscript published on 30 August 2019 | PP: 3125-3129 | Volume-8 Issue-10, August 2019 | Retrieval Number: J94530881019/19©BEIESP | DOI: 10.35940/ijitee.J9453.0881019
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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: Social media plays a major role in several things in our life. Social media helps all of us to find some important news with low price. It also provides easy access in less time. But sometimes social media gives a chance for the fast-spreading of fake news. So there is a possibility that less quality news with false information is spread through the social media. This shows a negative impact on the number of people. Sometimes it may impact society also. So, detection of fake news has vast importance. Machine learning algorithms play a vital role in fake news detection; Especially NLP (Natural Language Processing) algorithms are very useful for detecting the fake news. In this paper, we employed machine learning classifiers SVM, K-Nearest Neighbors, Decision tree, Random forest. By using these classifiers we successfully build a model to detect fake news from the given dataset. Python language was used for experiments.
Index Terms: Fake News, Machine Learning, Python.
Scope of the Article: Machine Learning