Hoax News Detection Using Convolutional Neural Network

Pranay Kamble; Aditya Dighe; Pallavi Naik; Shraddha Subhedar

doi:10.37591/joosdt.v7i2.2564

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.