JOURNAL ARTICLE

Detection of Fake News using Recurrent Neural Network

G. AnushaG. PraveenDubbala MounikaU. Sai KrishnaR. Cristin

Year: 2022 Journal:   2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pages: 1-5

Abstract

Fake news of social media is growing rapidly. The exponential growth and clean get right of entry to of the facts available on social media networks has made it elaborate to distinguish among fake and real news. Detecting fake news is very important. To identify the fake news detection techniques are proposed in Machine Learning and Deep Learning. In this Recurrent Neural Network method is used to determine whether or not the information is actual or fake information. Fake news will mislead and create wrong perceptions among the people. This paper explores different textual properties which are used to distinguish between real and fake news. In this, datasets of fake and true news are used to train the model using proposed algorithm. The accuracy of the model will show the efficiency of the system

Keywords:
Fake news Computer science Social media Artificial neural network Artificial intelligence Recurrent neural network Perception Machine learning Internet privacy World Wide Web Psychology

Metrics

4
Cited By
1.32
FWCI (Field Weighted Citation Impact)
15
Refs
0.82
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Misinformation and Its Impacts
Social Sciences →  Social Sciences →  Sociology and Political Science
Spam and Phishing Detection
Physical Sciences →  Computer Science →  Information Systems
Advanced Malware Detection Techniques
Physical Sciences →  Computer Science →  Signal Processing

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