Deep Learning and Natural Language Processing for fake news detection: A Survey

2021 ◽  
Author(s):  
Aditya Chokshi ◽  
Rejo Mathew
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.


News is a routine in everyone's life. It helps in enhancing the knowledge on what happens around the world. Fake news is a fictional information madeup with the intension to delude and hence the knowledge acquired becomes of no use. As fake news spreads extensively it has a negative impact in the society and so fake news detection has become an emerging research area. The paper deals with a solution to fake news detection using the methods, deep learning and Natural Language Processing. The dataset is trained using deep neural network. The dataset needs to be well formatted before given to the network which is made possible using the technique of Natural Language Processing and thus predicts whether a news is fake or not.


Spreading of fake news in online social media is a major nuisance to the public and there is no state of art tool to detect whether a news is a fake or an original one in an automated manner. Hence, this paper analyses the online social media and the news feeds for detection of fake news. The work proposes solution using Natural Language Processing and Deep Learning techniques for detecting the fake news in online social media.


Designs ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 42
Author(s):  
Eric Lazarski ◽  
Mahmood Al-Khassaweneh ◽  
Cynthia Howard

In recent years, disinformation and “fake news” have been spreading throughout the internet at rates never seen before. This has created the need for fact-checking organizations, groups that seek out claims and comment on their veracity, to spawn worldwide to stem the tide of misinformation. However, even with the many human-powered fact-checking organizations that are currently in operation, disinformation continues to run rampant throughout the Web, and the existing organizations are unable to keep up. This paper discusses in detail recent advances in computer science to use natural language processing to automate fact checking. It follows the entire process of automated fact checking using natural language processing, from detecting claims to fact checking to outputting results. In summary, automated fact checking works well in some cases, though generalized fact checking still needs improvement prior to widespread use.


Author(s):  
K.G.C.M Kooragama ◽  
L.R.W.D. Jayashanka ◽  
J.A. Munasinghe ◽  
K.W. Jayawardana ◽  
Muditha Tissera ◽  
...  

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