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Hoax News Detection Using Convolutional Neural Network

Pranay Kamble, Aditya Dighe, Pallavi Naik, Shraddha Subhedar

Abstract


In this paper our objective is to build a classifier that can predict whether a piece of news is Hoax or not based only its content, thereby approaching the problem from a purely deep learning perspective by technique models like LSTM(GRU), Naive Bayes and CNN. We will show the difference and analysis of results by applying them to the dataset Hoax_news which is available on kaggle.com. We found that the results are close, but CNN is the best of our results that reached (0.982) followed by Naive bayes(0.8644) and LSTM-GRU(0.916).

Keywords: Deep Learning; LSTM (longshort-term memories); GRU (Gated Recurrent Unit); CNN(Convolutional Neural Networks), technology.

Cite this Article: Aditya Dighe, Pallavi Naik, Pranay Kamble, Shraddha Subhedar. Hoax News Detection using Convolutional Neural Network.Journal of Operating Systems Development & Trends. 2020; 7(2): 19–23p.


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DOI: http://dx.doi.org/10.37591%2Fjoosdt.v7i2.2564

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