Savita, Vaishnavi S, Vaishnavi N, Shruti Suman
In our modern era where the internet is ubiquitous, everyone relies on various online resources for news. Along with the increase in the use of social media platforms like Facebook, Twitter, etc. news spread rapidly among millions of users within a very short span of time. The spread of fake news has far-reaching consequences like the creation of biased opinions to swaying election outcomes for the benefit of certain candidates. Moreover, spammers use appealing news headlines to generate revenue using advertisements via click baits. This project aim to perform binary classification of various news articles available online with the help of concepts pertaining to Artificial Intelligence, Natural Language Processing and Machine Learning. We aim to provide the user with the ability to classify the news as fake or real and also check the authenticity of the website publishing the news. Due to easy access, rapid growth, and proliferation of the information available through regular news mediums or social media, it is becoming easy for people to look for news and consume it. These days a lot of information is being shared over social media and we are not able to differentiate between which information is Fake and which is legitimacy. For publishing a news in social media the cost is low, easy access. The extension spread of fake news has the potential for extremely negative impact on individuals and society. The goal of this project is to create an efficient machine learning algorithm for identifying the fake news.
Article Details
Unique Paper ID: 156152

Publication Volume & Issue: Volume 9, Issue 2

Page(s): 914 - 917
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