FAKE NEWS DETECTION | 3/4 BTECH CSE | WISTM.ENGG COLLEGE

Fake news detection:
Fake news has grown quickly in the last decade, with social media playing an important
role. For a variety of causes, false information can be spread. Some are exclusively
intended to increase the number of clicks and visits to a website. Others, in order to
manipulate public opinion toward or away from political or economical issues. For
instance, businesses and institutions' internet reputations can be influenced. Fake health
news on social media is a health concern to the entire planet. An abundance of
information, some of it accurate, some of it not, made it difficult for people to find
reliable sources and trustworthy information when they needed it. The development of
doubt, dread, anxiety, and bigotry on a scale not seen in earlier epidemics is one of the
repercussions of disinformation overload.
We provide a novel approach and tool for detecting fake news in this research,
which employs:
i. The process of heating and analyzing text in order to remove stop words and special
characters is known as text preprocessing.
ii. Text encoding consists of a bag of words and an N-gram, followed by TF-IDF.
iii. Characteristic extraction: this allows for more precise detection of bogus data. We use
the source of the news, the author, the date, and the feeling conveyed by the content as
news aspects.
iv. Support vector machine (SVM): This is a supervised machine learning method for
classifying new data.