Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16526
Title: Fake News Detection Using Machine Learning Algorithms
Authors: Babu, Tina
Nair, Rekha R
Challa, Adithya
Srikanth, Rahul
Aravindan, Sri Sai
Suhas S
Keywords: Context Free Grammar
Fake News
Natural Language Processing
Response Generation
Self-Learning
Stochastic Gradient Decent
Issue Date: 2023
Publisher: 2023 International Conference on New Frontiers in Communication, Automation, Management and Security, ICCAMS 2023
Institute of Electrical and Electronics Engineers Inc.
Citation: pp. 1-7
Abstract: The spread of false news threatens news and information sources, especially in Indian politics. We present a machine learning-based strategy to identify false news by vectorizing and tokenizing news headlines using a pre-defined dataset of authentic and fraudulent news items. We want to create a model that can properly identify news stories by textual content, separating propaganda from real news. Our technique is tested on a benchmark dataset of news items. Our suggested technique outperforms various state-of-the-art false news detection algorithms in the literature. Our methodology can prevent false news and safeguard news and information sources in Indian politics. This technique is versatile and successful for identifying and reducing the impact of false news across several topics and languages. © 2023 IEEE.
URI: https://doi.org/10.1109/ICCAMS60113.2023.10525971
https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16526
ISBN: 9798350317060
Appears in Collections:Conference Papers

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