Abstract:
A vast quantity of data and information are available on the internet. Because the internet
is so widely available and has resulted in a tremendous growth in the number of online
news, people are interested in reading news from online news portals. Online news
portals include things like Facebook, Twitter, WhatsApp, Telegram, Instagram, blogs,
and more. Both the quantity of news-on-news websites and the number of readers is
increasing. But how real is online news today is a matter of thought. A huge amount of
fake news is being spread in newspapers and online due to various yellow journalists.
Which is having an adverse effect on society. As a result, there are many kinds of
instability, bad politics, etc. problems are being created in the country. If this situation
continues, our country and society will go to hell. The only solution is to ensure that
yellow journalists do not spread fake news. But despite all the vigilance, fake news will
spread. We can solve this by using artificial intelligence, for example, by employing
various machine learning and deep learning algorithms, we can identify bogus news and
take precautions against it. In this paper, fake news is detected using 4 deep learning
algorithms like RNN, LSTM, BiLSTM, GRU model and 1 machine learning algorithm
BERT model. RNN has an accuracy of 94.58%, LSTM has an accuracy of 92.84%,
BiLSTM has an accuracy of 94.29%, GRU has an accuracy of 93.22% and BERT has an
accuracy of 95%. The BERT model has the highest accuracy of 95% among all models.
