Fake News Detector
Date
2021-03-30
Journal Title
Journal ISSN
Volume Title
Publisher
Department of Computer Science and Engineering (CSE), Islamic University of Technology (IUT), Board Bazar, Gazipur-1704, Bangladesh
Abstract
With the recent social media boom, the spread of fake news has become a great
concern for everybody. It has been used to manipulate public opinions, influence
the election - most notably the US Presidential Election of 2016, incite hatred and
riots like the genocide of the Rohingya population. A 2018 MIT study found that
fake news spreads six times faster on Twitter than real news. The credibility and
trust in the news media are at an all-time low. It is becoming increasingly difficult
to determine which news is real and which is fake. Various machine learning
methods have been used to separate real news from fake ones. In this study, we
tried to accomplish that using Passive Aggressive Classifier, LSTM and natural
language processing. There are lots of machine learning models but these two
have shown better progress.
Now there is some confusion present in the authenticity of the correctness. But it
definitely opens the window for further research. There are some of the aspects that
has to be kept in mind considering the fact that fake news detection is not only a
simple web interface but also a quite complex thing that includes a lot of backend
work.
Description
Supervised by
Mr. Md. Hamjajul Ashmafee,
Lecturer,
Department of Computer Science and Engineering(CSE)
Islamic University of Technology(IUT),
Board Bazar, Gazipur-1704. Bangladesh
Keywords
Citation
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