Research Article
Detection of Fake News using Machine Learning Models
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 183 - Issue 47 |
| Published: Jan 2022 |
| Authors: Velivela Durga Lakshmi, Ch Sita Kumari |
10.5120/ijca2022921874
|
Velivela Durga Lakshmi, Ch Sita Kumari . Detection of Fake News using Machine Learning Models. International Journal of Computer Applications. 183, 47 (Jan 2022), 22-27. DOI=10.5120/ijca2022921874
@article{ 10.5120/ijca2022921874,
author = { Velivela Durga Lakshmi,Ch Sita Kumari },
title = { Detection of Fake News using Machine Learning Models },
journal = { International Journal of Computer Applications },
year = { 2022 },
volume = { 183 },
number = { 47 },
pages = { 22-27 },
doi = { 10.5120/ijca2022921874 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2022
%A Velivela Durga Lakshmi
%A Ch Sita Kumari
%T Detection of Fake News using Machine Learning Models%T
%J International Journal of Computer Applications
%V 183
%N 47
%P 22-27
%R 10.5120/ijca2022921874
%I Foundation of Computer Science (FCS), NY, USA
Abstract
In the present-day scenario, it is becoming a big problem to find whether a piece of news is real or fake. It is causing great loss to the individual and organization. The news articles can be from news channels or any other sources. In this project, the fake news is detected based on text, title, and author as parameters and converting them into vectors using Term Frequency- Inverse Document Frequency (TF-IDF) and Count vectorizers. On the vectors, PCA was applied to reduce the dimensions. The reduced vectors were given as input to the supervised machine learning algorithms. The resultant performance of algorithms was analyzed based on accuracy, precision, and recall. Hence, Random Forest classifier along with Count vectorizer gives the best technique for detection of the authenticity of the news.
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