Optimized Deep Learning Techniques for the Detection and Identification of Fake News in Digital Media

Narmadha Devi A. S., K. Sivakumar, V. Sheeja Kumari

2025

Abstract

The exponential expansion of social media has greatly accelerated the dissemination of disinformation, endangering public safety and undermining faith in news outlets and government agencies. The authors of this work suggest using deep learning to identify false news posts on Twitter. The methodology involves pre-processing raw data through stop word removal, stemming using Porter’s Algorithm, and tokenization with the N-gram model. The detection model employs Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), and AdaBoost algorithms. Results indicate that LSTM outperforms CNN and AdaBoost, achieving an accuracy of 99.24%, specificity of 99.2%, and sensitivity of 98.67% in fake news detection.

Paper Citation

in Harvard Style

S. N., Sivakumar K. and Kumari V. (2025). Optimized Deep Learning Techniques for the Detection and Identification of Fake News in Digital Media. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 506-511. DOI: 10.5220/0013932100004919

in Bibtex Style

@conference{icrdicct`2525,
author={Narmadha S. and K. Sivakumar and V. Kumari},
title={Optimized Deep Learning Techniques for the Detection and Identification of Fake News in Digital Media},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={506-511},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013932100004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Optimized Deep Learning Techniques for the Detection and Identification of Fake News in Digital Media
SN - 978-989-758-777-1
AU - S. N.
AU - Sivakumar K.
AU - Kumari V.
PY - 2025
SP - 506
EP - 511
DO - 10.5220/0013932100004919
PB - SciTePress