Course Content

ABSTRACT

 

Information sharing on the web particularly via web based networking media is increasing. Ability to identify, evaluate and address such information is significantly important. Fake information deliberately created is purposefully or unintentionally engendered over the internet. This is affecting a larger group of society who are blinded by technology. Fake news has been a problem ever since the internet boomed. The very network that allows us to know what is happening globally is the perfect breeding ground for malicious and fake news. Combating this fake news is important because the world's view is shaped by information. Fake news attracted attention both from the public and the academic communities and represents a phenomenon that has a significant impact on our social life, especially on the political world. Further more, fake news phenomenon provide an opportunity for malicious parties to manipulate public opinion and events such as elections .People not only make important decisions based on information but also form their own opinions. If this information is false it can have devastating consequences. Verifying each  news one by one by a human being is completely unfeasible

So we proposed a system with the help of machine learning techniques, NLP techniques like count vectorizer, TF-IDF Transformer and Machine learning  algorithms like Logistic Regression and Naïve Bayes to predict the News is Fake or not and based on news data entered by the user in the front end.

INTRODUCTION

Fake news is a false piece of information. In today's world, with the increase in spread of fake news from social media and various other sources it is becoming very important to be able to categorize between real news and fake news. Fake news is a major factor in inciting riots, carnage, mob lynchings and other social-economic disturbances. Any piece of Fake news can be created to deliberately misinform or deceive readers, promote a biased point of view, particular cause or agenda, and even for the entertainment. Fake news can be promoted by unauthenticated user ID, social media, printing of fake news in newspapers maybe due to political pressure and many more. Spreading of fake news can cause discontent among people, riots, and even cause loss of trust between two people and even nations. It also has a huge possibility to exploit general public thinking in a completely different manner. News and media coverage gets hugely distorted due to initialization and spread of fake news. Where news can be a boon, fake news is a bane to the society. These days there are many anti-social elements, which may instigate and propagate fake news that may cause societal instability in many layers of social-economic-politicalcultural aspects. Many instances of religion clash have been attributed to such fake news. The Internet is an abundance of data and exceptionally worthwhile for different reasons. Due to the overwhelming information available on the internet, one must be cautious about the originality . To connect with family, friends, fellow workers the main medium is social media. Every user is sharing their feelings or information in the different forms like audio, video or text . Fake information’s are deliberately created and are purposefully or unexpectedly engendered over the internet. Creation and consumption of information over the internet have increased over time even if it's fake or real. Thus impacting groups of society who are large consumers of the internet and blinded by technology. Classification of any news item /post / blog into fake or real one has generated great interest from researchers around the globe. Several research studies have been carried out to find effect of falsified and fabricated news on masses and reactions of people upon coming through such news items. Falsified news or fabricated pos newst is any textual or non-textual content that is fake and is generated so the readers will start believing in something which is not true. Consumers cannot access accurate news due to the associated costs, therefore, fake news gains attention since it is cheaper to distribute than precise information. Fake news has a lot of private and social costs associated with it since it makes it difficult for customers to know about the truth and can affect decisions like votes.

 

So we proposed a system with the help of machine learning techniques, NLP techniques like count vectorizer, TF-IDF Transformer and Machine learning  algorithms like Logistic Regression and Naïve Bayes to predict the News is Fake or not and based on news data entered by the user in the front end.

 

 

 

 

 

 

 

 

 

Objective

The main aim of this project is to detect fake news using machine learning techniques, NLP techniques and machine learning algorithms like logistic regression and naïve bayes with good accuracy based on news data entered by the user in the front end.

 

 

 

 

 

Problem Statement

 

Fake information’s are deliberately created and are purposefully or unexpectedly engendered over the internet. Creation and consumption of information over the internet have increased over time even if it's fake or real. Thus impacting groups of society who are large consumers of the internet and blinded by technology. So detecting fake news is important.

 

 

 

Proposed System:

 

We proposed a system with the help of machine learning techniques, NLP techniques like count vectorizer, TF-IDF Transformer and Machine learning  algorithms like Logistic Regression and Naïve Bayes to predict the News is Fake or not and based on news data entered by the user in the front end.