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Fake News Detector: FND
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 176 - Number 10 |
| Year of Publication: 2020 |
| Authors: Pravin P. Kharat, Sanyam Sharma, Sayali Tambe, Deepali Vora |
10.5120/ijca2020920002
|
Pravin P. Kharat, Sanyam Sharma, Sayali Tambe, Deepali Vora . Fake News Detector: FND. International Journal of Computer Applications. 176, 10 ( Apr 2020), 13-17. DOI=10.5120/ijca2020920002
Abstract
The idea focuses on providing the information on whether the news is real or fake and with distinguished information about the content or news headline provided by the user into the developed system. The user is a client or a customer, gets particular news or headline from any source which can be news providing application, news blog, website and social networking site; and upload the news content in the proposed system which is a web-based application. After uploading the news content or headline the user clicks the submit button which is available on the website. Then the content is processed accordingly and the metadata of the content is extracted. There are derived parameters on the basis of which calculation of news authenticity is done. The system also uses the Naive Bayes and Term Frequency-Inverse Document Frequency (TFIDF) algorithm which is used to predict the probability of different classes, based on various parameters or attributes. TFIDF i.e. Term Frequency-Inverse Document Frequency is an algorithm used to transform the text into a meaningful representation of numbers. Based upon the parameters and using the respective algorithm the news authenticity is calculated and the result is uploaded. The final result states whether the news is real or fake news and is developed upon the parameters, metadata and algorithm which simultaneously gives the respective result to the user.
References
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