Deep Learning for Fake News Detection

Author(s):  
Deepak P ◽  
Tanmoy Chakraborty ◽  
Cheng Long ◽  
Santhosh Kumar G
Keyword(s):  
2021 ◽  
pp. 107614
Author(s):  
Monika Choudhary ◽  
Satyendra Singh Chouhan ◽  
Emmanuel S. Pilli ◽  
Santosh Kumar Vipparthi

Author(s):  
Ting-Hao Chang ◽  
Wei-Hung Tu ◽  
Jia-Wei Chang ◽  
Tien-Chi Huang ◽  
Yi-Xiang Luo

Author(s):  
Varalakshmi Konagala ◽  
Shahana Bano

The engendering of uncertain data in ordinary access news sources, for example, news sites, web-based life channels, and online papers, have made it trying to recognize capable news sources, along these lines expanding the requirement for computational instruments ready to give into the unwavering quality of online substance. For instance, counterfeit news outlets were observed to be bound to utilize language that is abstract and enthusiastic. At the point when specialists are chipping away at building up an AI-based apparatus for identifying counterfeit news, there wasn't sufficient information to prepare their calculations; they did the main balanced thing. In this chapter, two novel datasets for the undertaking of phony news locations, covering distinctive news areas, distinguishing proof of phony substance in online news has been considered. N-gram model will distinguish phony substance consequently with an emphasis on phony audits and phony news. This was pursued by a lot of learning analyses to fabricate precise phony news identifiers and showed correctness of up to 80%.


Author(s):  
Uma Maheswari Sadasivam ◽  
Nitin Ganesan

Fake news is the word making more talk these days be it election, COVID 19 pandemic, or any social unrest. Many social websites have started to fact check the news or articles posted on their websites. The reason being these fake news creates confusion, chaos, misleading the community and society. In this cyber era, citizen journalism is happening more where citizens do the collection, reporting, dissemination, and analyse news or information. This means anyone can publish news on the social websites and lead to unreliable information from the readers' points of view as well. In order to make every nation or country safe place to live by holding a fair and square election, to stop spreading hatred on race, religion, caste, creed, also to have reliable information about COVID 19, and finally from any social unrest, we need to keep a tab on fake news. This chapter presents a way to detect fake news using deep learning technique and natural language processing.


2020 ◽  
Vol 1 (3) ◽  
Author(s):  
Aman Agarwal ◽  
Mamta Mittal ◽  
Akshat Pathak ◽  
Lalit Mohan Goyal

Sign in / Sign up

Export Citation Format

Share Document