Paper Title

Fake news detection and fact verification using machine learning

Authors

Tushar Sonawane , Aditya Bhadale , Shubham Karale , Ajit Vaykule , Mayuri Vengurlekar

Keywords

smartphone, disaster alert, remote sensing, GPS, PS

Abstract

There are many ways one could effort to observe fake or partial intelligence on the internet. However, we awareness our execution based on stance detection soured the sterling flexibility and are dependability without having to get into the garment of labeling individual assertion as true or false. Rather we purpose for a more general movement classifying articles from chartless sources as mostly agreeing or generally disagree with sources of known (high and low) credibility. Moreover, our implementation is particularly compelling because we can evaluate user input as either a link to an article OR as any absolute claim to be fact restrained like (Obama is not a US citizen). In this way our system acts as a fact-finding activity engine and twist links to applicable articles along with that article’s stance (agree/disagree/is-neutral) on that topic! Our program offers enormous investigation and discovery possible to users as well as merely checking assertion. We wanted to make an easy-to-use system to detect the believability of a user’s claim or article, based on the thought of stance detection.

How To Cite

"Fake news detection and fact verification using machine learning", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 3, page no.b437-b441, March-2023, Available :https://ijnrd.org/papers/IJNRD2303150.pdf

Issue

Volume 8 Issue 3, March-2023

Pages : b437-b441

Other Publication Details

Paper Reg. ID: IJNRD_188402

Published Paper Id: IJNRD2303150

Downloads: 000118835

Research Area: Computer Engineering 

Country: Pune, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2303150

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2303150

About Publisher

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJNRD (IJ Publication) Janvi Wave

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