Scalable System for Identifying and Flagging Misinformation Using AI/ML and DL

Year : 2026 | Volume : 13 | Issue : 02 | Page : 33 40
By

P.B. Kudal,

Sharmad Shringarpure,

Shiksha Dubey,

  1. Research Scholar, Thakur Institute of Management Studies, Career Development & Research, Maharashtra, India
  2. Research Scholar, Thakur Institute of Management Studies, Career Development & Research, Maharashtra, India
  3. Assistant Professor, Thakur Institute of Management Studies, Career Development & Research, Maharashtra, India

Abstract

The fast spread of realistic fake media means we need to make a system to identify false information that can work with a lot of data. This system is called the Scalable Misinformation Identification System or SMIS for short. SMIS helps keep our society and democracy safe from the threats of news on the internet. The old ways of checking for news and simple machine learning models are not good enough to find the small clues in modern fake media that are made by advanced computers. The SMIS uses a Deep Learning framework that uses Transfer Learning to see which of the best Convolutional Neural Networks works the best. These networks are Xception, InceptionV3, ResNet50 and MobileNetV2. They are very good at finding the clues in fake media that are made by computers. The SMIS checks these networks to find the one for finding fake media. The results show that these complex models are much better than the ways of checking for fake news. They can find the clues that show when media has been manipulated. By choosing the model the SMIS can work very fast and can be used on the cloud. This means the SMIS can find media in real time. The SMIS is very important for keeping people trusting the news and making sure the information on the internet is true. The Scalable Misinformation Identification System is a tool for keeping our society safe from fake news, in a world where computers are making more and more of the media we see.

Keywords: Identifying misinformation, deep learning, transfer learning, detecting deepfakes, Xception, image classification

[This article belongs to Journal of Artificial Intelligence Research & Advances ]

How to cite this article: P.B. Kudal, Sharmad Shringarpure, Shiksha Dubey. Scalable System for Identifying and Flagging Misinformation Using AI/ML and DL. Journal of Artificial Intelligence Research & Advances. 2026; 13(02):33-40.
How to cite this URL: P.B. Kudal, Sharmad Shringarpure, Shiksha Dubey. Scalable System for Identifying and Flagging Misinformation Using AI/ML and DL. Journal of Artificial Intelligence Research & Advances. 2026; 13(02):33-40. Available from: https://journals.stmjournals.com/joaira/article=2026/view=260215

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Regular Issue Subscription Original Research
Volume 13
Issue 02
Received 10/03/2026
Accepted 26/06/2026
Published 30/06/2026
Publication Time 112 Days

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