Authors :
M. Madhu srija; E. Akhil; G. Nava Thej
Volume/Issue :
Volume 8 - 2023, Issue 4 - April
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://bit.ly/44Forbo
DOI :
https://doi.org/10.5281/zenodo.7905710
Abstract :
Fake news is a very dangerous problem for
society, and its dangers have become clear in recent years,
and research in this area is increasing, as evidenced by its
impact on public opinion in the 2016 US presidential
election. The dangers of fake news have social, political,
and economic dimensions, and psychology also affects
personality. This paper presents a solution to mitigate the
impact of these messages. The system is designed to detect
fake news and distinguish between them with less effort
and less time. Most of smartphone users prefer to read
social media news via internet. News websites publish
news and provide authoritative sources. The problem is
how to authenticate news and articles circulating in social
media such as WhatsApp groups, Facebook pages,
Twitter and other microblogging and social networking
sites. Believing rumours and pretending to be news is
harmful to society. Especially in a developing country like
India, it takes an hour to stop the rumours and focus on
the correct and authoritative news stories. This paper
presents a model and methodology for detecting fake
news. With the help of machine learning and natural
language processing, we aggregate the messages and later
try to use logistic regression to determine if the message is
real or fake. The model works well and defines the
accuracy of the results with 97.21% accuracy
Keywords :
fake news, machine leaning, accuracy, authoritative sources.
Fake news is a very dangerous problem for
society, and its dangers have become clear in recent years,
and research in this area is increasing, as evidenced by its
impact on public opinion in the 2016 US presidential
election. The dangers of fake news have social, political,
and economic dimensions, and psychology also affects
personality. This paper presents a solution to mitigate the
impact of these messages. The system is designed to detect
fake news and distinguish between them with less effort
and less time. Most of smartphone users prefer to read
social media news via internet. News websites publish
news and provide authoritative sources. The problem is
how to authenticate news and articles circulating in social
media such as WhatsApp groups, Facebook pages,
Twitter and other microblogging and social networking
sites. Believing rumours and pretending to be news is
harmful to society. Especially in a developing country like
India, it takes an hour to stop the rumours and focus on
the correct and authoritative news stories. This paper
presents a model and methodology for detecting fake
news. With the help of machine learning and natural
language processing, we aggregate the messages and later
try to use logistic regression to determine if the message is
real or fake. The model works well and defines the
accuracy of the results with 97.21% accuracy
Keywords :
fake news, machine leaning, accuracy, authoritative sources.