Automated Detection Of Fake News: A Machine Learning Approach

Prof. Somnath Mule; Swarali Kamble; Rashmi Kulkarni; Sunita Dange; Gausiya Shaikh; Shivani Parbat

Automated Detection Of Fake News: A Machine Learning Approach

May 2024

Vol-10, Issue-3

Paper ID: 24087

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Computer Engineering

Keywords

Online fake news Machine learning fake news Text Classification social media misinformation Logistic Regression

Abstract

The fake news on social media and various other media is wide spreading and is a matter of serious concern due to its ability to cause a lot of social and national damage with destructive impacts. This study focused on classifying fake news on social media with textual content (text classification).In this work, we propose to use natural language processing (NLP) techniques to analyze textual features and machine learning ensemble approach for automated classification of news articles and makes an analysis of the research related to fake news detection and explores the traditional machine learning models to choose the best, in order to create a model of a product with supervised machine learning algorithm, that can classify news as true or false. Experimental results demonstrate the effectiveness of the chosen methodologies, showcasing the system's potential as a reliable tool in combating fake news.

License

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Author Information

#	Name	Institute / Affiliation
1	Prof. Somnath Mule	MIT College Of Railway Engineering And Research , Barshi
2	Swarali Kamble	MIT College Of Railway Engineering And Research , Barshi
3	Rashmi Kulkarni	MIT College Of Railway Engineering And Research , Barshi
4	Sunita Dange	MIT College Of Railway Engineering And Research , Barshi
5	Gausiya Shaikh	MIT College Of Railway Engineering And Research , Barshi
6	Shivani Parbat	MIT College Of Railway Engineering And Research , Barshi

How to Cite

Use the following formats to cite this article in your research.

APA Style

Mule, Prof. Somnath, Kamble, Swarali, Kulkarni, Rashmi, Dange, Sunita, Shaikh, Gausiya, & Parbat, Shivani (2024). Automated Detection Of Fake News: A Machine Learning Approach. International Journal of Advance Research and Innovative Ideas In Education, 10(3), 4251-4257.

MLA Style

Mule, Prof. Somnath, et al. "Automated Detection Of Fake News: A Machine Learning Approach." International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 3, 2024, pp. 4251-4257.

IEEE Style

Prof. Somnath Mule, Swarali Kamble, Rashmi Kulkarni, Sunita Dange, Gausiya Shaikh, and Shivani Parbat, "Automated Detection Of Fake News: A Machine Learning Approach," International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 3, pp. 4251-4257, 2024.

Vancouver Style

Mule Prof. Somnath, Kamble Swarali, Kulkarni Rashmi, Dange Sunita, Shaikh Gausiya, Parbat Shivani. Automated Detection Of Fake News: A Machine Learning Approach. International Journal of Advance Research and Innovative Ideas In Education. 2024;10(3):4251-4257.

Harvard Style

Mule, Prof. Somnath, Kamble, Swarali, Kulkarni, Rashmi, Dange, Sunita, Shaikh, Gausiya, & Parbat, Shivani (2024) 'Automated Detection Of Fake News: A Machine Learning Approach', International Journal of Advance Research and Innovative Ideas In Education, 10(3), pp. 4251-4257.

Chicago Style

Mule, Prof. Somnath, et al. "Automated Detection Of Fake News: A Machine Learning Approach." International Journal of Advance Research and Innovative Ideas In Education 10, no. 3 (2024): 4251-4257.

Turabian Style

Mule, Prof. Somnath, et al. "Automated Detection Of Fake News: A Machine Learning Approach." International Journal of Advance Research and Innovative Ideas In Education 10, no. 3 (2024): 4251-4257.